We present a novel method for the measurement of the similarity between aggregates of scanpaths. This may be thought of as a solution to the “average scanpath” problem. As a by-product of this method, we derive a classifier for groups of scanpaths drawn from various classes. This capability is empirically demonstrated using data gathered from an experiment in an attempt to automatically determine expert/novice classification for a set of visual tasks.
Jarodzka A Vector Based, Multidimensional Scanpath Similarity MeasureKalle
A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are. Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures - the Levenshtein distance and attention map correlation.
Dorr Space Variant Spatio Temporal Filtering Of Video For Gaze Visualization ...Kalle
We introduce an algorithm for space-variant filtering of video based on a spatio-temporal Laplacian pyramid and use this algorithm to render videos in order to visualize prerecorded eye movements. Spatio-temporal contrast and colour saturation are reduced as a function of distance to the nearest gaze point of regard, i.e. nonfixated, distracting regions are filtered out, whereas fixated image regions remain unchanged. Results of an experiment in which the eye movements of an expert on instructional videos are visualized with this algorithm, so that the gaze of novices is guided to relevant
image locations, show that this visualization technique facilitates the novices’ perceptual learning.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Blignaut Visual Span And Other Parameters For The Generation Of HeatmapsKalle
Although heat maps are commonly provided by eye-tracking and visualization tools, they have some disadvantages and caution must be taken when using them to draw conclusions on eye tracking results. It is motivated here that visual span is an essential component of visualizations of eye-tracking data and an algorithm is proposed to allow the analyst to set the visual span as a parameter prior to generation of a heat map.
Although the ideas are not novel, the algorithm also indicates how transparency of the heat map can be achieved and how the color gradient can be generated to represent the probability for an object to be observed within the defined visual span. The optional addition of contour lines provides a way to visualize separate intervals in the continuous color map.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Jarodzka A Vector Based, Multidimensional Scanpath Similarity MeasureKalle
A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are. Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures - the Levenshtein distance and attention map correlation.
Dorr Space Variant Spatio Temporal Filtering Of Video For Gaze Visualization ...Kalle
We introduce an algorithm for space-variant filtering of video based on a spatio-temporal Laplacian pyramid and use this algorithm to render videos in order to visualize prerecorded eye movements. Spatio-temporal contrast and colour saturation are reduced as a function of distance to the nearest gaze point of regard, i.e. nonfixated, distracting regions are filtered out, whereas fixated image regions remain unchanged. Results of an experiment in which the eye movements of an expert on instructional videos are visualized with this algorithm, so that the gaze of novices is guided to relevant
image locations, show that this visualization technique facilitates the novices’ perceptual learning.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Blignaut Visual Span And Other Parameters For The Generation Of HeatmapsKalle
Although heat maps are commonly provided by eye-tracking and visualization tools, they have some disadvantages and caution must be taken when using them to draw conclusions on eye tracking results. It is motivated here that visual span is an essential component of visualizations of eye-tracking data and an algorithm is proposed to allow the analyst to set the visual span as a parameter prior to generation of a heat map.
Although the ideas are not novel, the algorithm also indicates how transparency of the heat map can be achieved and how the color gradient can be generated to represent the probability for an object to be observed within the defined visual span. The optional addition of contour lines provides a way to visualize separate intervals in the continuous color map.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Shadow Detection and Removal using Tricolor Attenuation Model Based on Featur...ijtsrd
Presently present TAM FD, a novel expansion of tricolor constriction model custom fitted for the difficult issue of shadow identification in pictures. Past strategies for shadow discovery center on learning the neighborhood appearance of shadow areas, while utilizing restricted nearby setting thinking as pairwise possibilities in a Conditional Random Field. Interestingly, the proposed methodology can display more elevated amount connections and worldwide scene attributes. We train a shadow locator that relates to the generator of a restrictive TAM, and expand its shadow precision by consolidating the run of the mill TAM misfortune with an information misfortune term utilizing highlight descriptor. Shadows happen when articles impede direct light from a wellspring of enlightenment, which is generally the sun. As indicated by the rule of arrangement, shadows can be separated into cast shadow and self shadow. Cast shadow is planned by the projection of articles toward the light source self shadow alludes to the piece of the item that isnt enlightened. For a cast shadow, the piece of it where direct light is totally hindered by an article is named the umbra, while the part where direct light is mostly blocked is named the obscuration. On account of the presence of an obscuration, there wont be an unequivocal limit among shadowed and non shadowed regions the shadows cause incomplete or all out loss of radiometric data in the influenced zones, and therefore, they make errands like picture elucidation, object identification and acknowledgment, and change recognition progressively troublesome or even inconceivable. SDI record improves by 1.76 . Shading segment record for safeguard shading difference during evacuation of shadow procedure is improved by 9.75 . Standardize immersion esteem discovery file NSVDI is improve by 1.89 for distinguish shadow pixel. Rakesh Dangi | Anjana Nigam ""Shadow Detection and Removal using Tricolor Attenuation Model Based on Feature Descriptor"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25127.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/25127/shadow-detection-and-removal-using-tricolor-attenuation-model-based-on-feature-descriptor/rakesh-dangi
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A CONTENT BASED WATERMARKING SCHEME USING RADIAL SYMMETRY TRANSFORM AND SINGU...cscpconf
The Watermarking techniques represent actually a very important issue in digital multimedia
content distribution. To protect digital multimedia content we embed an invisible watermark
into images which facilitate the detection of different manipulations, duplication, illegitimate
distributions of these images. In this paper we present an approach to embedding invisible
watermarks into color images using a robust transform of images that is the Radial symmetry
transform. The watermark is inserted in blocs of eight pixels large of the blue channel using the
Singular Value Decomposition (SVD) of these blocs and those of the radial symmetry transform.
The insertion in the blue channel is justified when we know that many works states that the
human visual system is less sensible to perturbation in the blue channel of the image. Results
obtained after tests show that the imperceptibility of the watermark using this approach is good
and its robustness face to different attacks leads to think that the proposed approach is a very
promising one.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
In this chapter author discusses a number of popular visualization methods for vector datasets: vector glyphs, vector color-coding, displacement plots, stream objects, texture-based vector visualization, and the simplified representation of vector fields.
Section 6.5 presents stream objects, which use integral techniques to construct paths in vector fields. Section 6.7 discusses a number of strategies for simplified representation of vector datasets. Section 6.8 presents a number of illustrative visualization techniques for vector fields, which offer an alternative mechanism for simplified representation to the techniques discussed in Section 6.7 Chapter presents also feature detection methods, algorithm for computing separatrices on field’s topology, and top-down and bottom-up field decomposition methods.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
We presented a number of fundamental methods for visualizing scalar data: color mapping, contouring, slicing, and height plots. Color mapping assigns a color as a function of the scalar value at each point of a given domain. Contouring displays all points within a given two- or three-dimensional domain that have a given scalar value. Height plots deform the scalar dataset domain in a given direction as a function of the scalar data. The main advantages of these techniques are that they produce intuitive results, easily understood by users, and they are simple to implement. However, such techniques also have s number of restrictions.
State-of-the-art Clustering Techniques: Support Vector Methods and Minimum Br...Vincenzo Russo
Clustering is an automatic learning technique aimed at grouping a set of objects into subsets or clusters. The goal is to create clusters that are coherent internally, but substantially different from each other. In plain words, objects in the same cluster should be as similar as possible, whereas objects in one cluster should be as dissimilar as possible from objects in the other clusters.
Clustering is an unsupervised learning technique, because it groups objects in clusters without any additional information: only the information provided by data is used and no human operation adds bits of information to improve the learning.
The application domains are manifold. For example, the grouping of text documents: in this case the goal is the construction of groups of documents related to each other, i.e. documents treating the same argument.
The goal of this thesis is studying in depth state-of-the-art and experimental clustering techniques. We consider two techniques. The first is known as Minimum Bregman Information principle. Such a principle generalizes the classic relocation scheme adopted yet by K-means, in order to allow the employment of a rich gamma of divergence functions said just Bregman divergences. A new, more general, clustering scheme was developed on top of this principle. Moreover, a co-clustering scheme is formulated too. This leads to an important generalization, as we will see in the sequel.
The second approach is the Support Vector Clustering. It is a clustering process which relies on the state-of-the-art of the learning machines: the Support Vector Machines. The Support Vector Clustering is currently subject of active research, as it still is in early stage of development. We have accurately analyzed such a clustering method and we have also provided some contributions which allow allow a reduction in the number of iterations and in the computational complexity and a gain in accuracy.
The main application domains we have dealt to are the text mining and the astrophysics data mining. Within these application domains we have verified and accurately analyzed the properties of both methodologies, by means of dedicated experiments.
The results are given in terms of robustness w.r.t. the missing values, the dimensionality reduction, the robustness w.r.t. the noise and the outliers, the ability of describing clusters of arbitrary shapes.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
Shadow detection and removal from single images of natural scenes is the main problem. Hence, Shadow detection and removal remained a challenging task. Significant research carried out on different shadow detection techniques. Over the last decades several approaches were introduced to deal with shadow detection and removal. Shadows are visual phenomena which happen when an area in the scene is occluded from the primary light source e.g. sun . Shadows are everywhere around us and we are rarely Confused by their presence. This article provides an overview of various methods used for shadow detection and removal using some main components like texture analysis, color information, Gaussian mixture model GMM and deterministic non model based approach. Texture Color This paper is aimed to provide a survey on various algorithms and methods of shadow detection and removal with their comparative study. Avinash Kumar Singh | Ankit Pandit ""Shadow Detection and Removal Techniques: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25201.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25201/shadow-detection-and-removal-techniques-a-perspective-view/avinash-kumar-singh
Shadow Detection and Removal in Still Images by using Hue Properties of Color...ijsrd.com
This paper involves the review of the Shadow Detection and Removal in still images. No prior information has been used such as background images etc. for finding the shadows. It is a very challenging issue for the computer vision system that shadows effect the perception of artificial intelligence based machines in appropriately detecting the particular object as shadows also picked by them and detected as false positive objects. Also in surveillance, it affects the proper tracking of humans such as at airports. We proposed a method to remove shadows which eliminates the shadow much better than existed methods. RGB space has been used of the images and some morphological operations also applied to get better results.
Visual Attention Convergence Index for Virtual Reality ExperiencesPawel Kobylinski
The paper introduces a novel quantitative method in the domain of eye tracking (ET) for virtual reality (VR). The method might be of interest to researchers on the human factor in VR, behavioral psychologists, and designers of VR experiences. Several mathematical formulas describing a novel index quantifying convergence of visual attention are introduced. The index is based on recently developed distance variance, a function of distances between observations in metric spaces. An aggregated version of the visual attention convergence index introduced in the paper allows to measure the effectiveness of any system of attentional cues employed by a designer to guide the attention of VR experience participants along an intended narration line. An individual version of the index allows to capture individual differences in the convergence of visual attention across participants. Possibilities for real-life and academic usage of the index are discussed and example results of application to real VR ET data are summarized.
Cite as:
Kobylinski P., Pochwatko G. (2020) Visual Attention Convergence Index for Virtual Reality Experiences. In: Ahram T., Taiar R., Colson S., Choplin A. (eds) Human Interaction and Emerging Technologies. IHIET 2019. Advances in Intelligent Systems and Computing, vol 1018. Springer, Cham
https://link.springer.com/chapter/10.1007/978-3-030-25629-6_48
A New Watermarking Algorithm Based on Image Scrambling and SVD in the Wavelet...IDES Editor
A new watermarking algorithm which is based on
image scrambling and SVD in the wavelet domain is discussed
in this paper. In the proposed algorithm, chaotic signals are
generated using logistic mapping and are used for scrambling
the original watermark. The initial values of logistic mapping
are taken as private keys. The covert image is decomposed
into four bands using integer wavelet transform; we apply
SVD to each band and embed the
Land Cover Feature Extraction using Hybrid Swarm Intelligence Techniques - A ...IDES Editor
The findings of recent studies are showing strong
evidence to the fact that some aspects of biogeography can be
applied to solve specific problems in science and engineering.
The proposed work presents a hybrid biologically inspired
technique that can be adapted according to the database of
expert knowledge for a more focused satellite image
classification. The paper also presents a comparative study of
our hybrid intelligent classifier with the other recent Soft
Computing Classifiers such as ACO, Hybrid Particle Swarm
Optimization-cAntMiner (PSO-ACO2), Fuzzy sets, Rough-
Fuzzy Tie up and the Semantic Web Based Classifiers and
the traditional probabilistic classifiers such as the Minimum
Distance to Mean Classifier (MDMC) and the Maximum
Likelihood Classifier (MLC).
SHARP OR BLUR: A FAST NO-REFERENCE QUALITY METRIC FOR REALISTIC PHOTOScsandit
There is an increasing demand on identifying the sharp and the blur photos from a burst of series or a mass of collection. Subjective assessment on image blurriness takes account of not only pixel variation but also the region of interest and the scene type. It makes measuring image sharpness in line with visual perception very challenging. In this paper, we devise a noreference image sharpness metric, which combines a set of gradient-based features adept in estimating Gaussian blur, out-of-focus blur and motion blur respectively. We propose a datasetadaptive logistic regression to build the metric upon multiple datasets, where over half of the samples are realistic blurry photos. Cross validation confirms that our metric outperforms thestate- of-the-art methods on the datasets with a total of 1577 images. Moreover, our metric is very fast, suitable for parallelization, and has the potential of running on mobile or embedded devices.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
Chapter provides an overview of a number of methods for visualizing tensor data. It explains principal component analysis as a technique used to process a tensor matrix and extract from it information that can directly be used in its visualization. It forms a fundamental part of many tensor data processing and visualization algorithms. Section 7.4 shows how the results of the principal component analysis can be visualized using the simple color-mapping techniques. Next parts of the chapter explain how same data can be visualized using tensor glyphs, and streamline-like visualization techniques.
In contrast to Slicer, which is a more general framework for analyzing and visualizing 3D slice-based data volumes, the Diffusion Toolkit focuses on DT-MRI datasets, and thus offers more extensive and easier to use options for fiber tracking.
Liu Natural Scene Statistics At Stereo FixationsKalle
We conducted eye tracking experiments on naturalistic stereo images presented through a haploscope, and found that fixated
luminance contrast and luminance gradient were generally higher than randomly selected luminance contrast and luminance gradient, which agrees with previous literature. However we also found that the fixated disparity contrast and disparity gradient were generally lower than randomly selected disparity contrast and disparity gradient. We discuss the implications of this remarkable
result.
Shadow Detection and Removal using Tricolor Attenuation Model Based on Featur...ijtsrd
Presently present TAM FD, a novel expansion of tricolor constriction model custom fitted for the difficult issue of shadow identification in pictures. Past strategies for shadow discovery center on learning the neighborhood appearance of shadow areas, while utilizing restricted nearby setting thinking as pairwise possibilities in a Conditional Random Field. Interestingly, the proposed methodology can display more elevated amount connections and worldwide scene attributes. We train a shadow locator that relates to the generator of a restrictive TAM, and expand its shadow precision by consolidating the run of the mill TAM misfortune with an information misfortune term utilizing highlight descriptor. Shadows happen when articles impede direct light from a wellspring of enlightenment, which is generally the sun. As indicated by the rule of arrangement, shadows can be separated into cast shadow and self shadow. Cast shadow is planned by the projection of articles toward the light source self shadow alludes to the piece of the item that isnt enlightened. For a cast shadow, the piece of it where direct light is totally hindered by an article is named the umbra, while the part where direct light is mostly blocked is named the obscuration. On account of the presence of an obscuration, there wont be an unequivocal limit among shadowed and non shadowed regions the shadows cause incomplete or all out loss of radiometric data in the influenced zones, and therefore, they make errands like picture elucidation, object identification and acknowledgment, and change recognition progressively troublesome or even inconceivable. SDI record improves by 1.76 . Shading segment record for safeguard shading difference during evacuation of shadow procedure is improved by 9.75 . Standardize immersion esteem discovery file NSVDI is improve by 1.89 for distinguish shadow pixel. Rakesh Dangi | Anjana Nigam ""Shadow Detection and Removal using Tricolor Attenuation Model Based on Feature Descriptor"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25127.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/25127/shadow-detection-and-removal-using-tricolor-attenuation-model-based-on-feature-descriptor/rakesh-dangi
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A CONTENT BASED WATERMARKING SCHEME USING RADIAL SYMMETRY TRANSFORM AND SINGU...cscpconf
The Watermarking techniques represent actually a very important issue in digital multimedia
content distribution. To protect digital multimedia content we embed an invisible watermark
into images which facilitate the detection of different manipulations, duplication, illegitimate
distributions of these images. In this paper we present an approach to embedding invisible
watermarks into color images using a robust transform of images that is the Radial symmetry
transform. The watermark is inserted in blocs of eight pixels large of the blue channel using the
Singular Value Decomposition (SVD) of these blocs and those of the radial symmetry transform.
The insertion in the blue channel is justified when we know that many works states that the
human visual system is less sensible to perturbation in the blue channel of the image. Results
obtained after tests show that the imperceptibility of the watermark using this approach is good
and its robustness face to different attacks leads to think that the proposed approach is a very
promising one.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
In this chapter author discusses a number of popular visualization methods for vector datasets: vector glyphs, vector color-coding, displacement plots, stream objects, texture-based vector visualization, and the simplified representation of vector fields.
Section 6.5 presents stream objects, which use integral techniques to construct paths in vector fields. Section 6.7 discusses a number of strategies for simplified representation of vector datasets. Section 6.8 presents a number of illustrative visualization techniques for vector fields, which offer an alternative mechanism for simplified representation to the techniques discussed in Section 6.7 Chapter presents also feature detection methods, algorithm for computing separatrices on field’s topology, and top-down and bottom-up field decomposition methods.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
We presented a number of fundamental methods for visualizing scalar data: color mapping, contouring, slicing, and height plots. Color mapping assigns a color as a function of the scalar value at each point of a given domain. Contouring displays all points within a given two- or three-dimensional domain that have a given scalar value. Height plots deform the scalar dataset domain in a given direction as a function of the scalar data. The main advantages of these techniques are that they produce intuitive results, easily understood by users, and they are simple to implement. However, such techniques also have s number of restrictions.
State-of-the-art Clustering Techniques: Support Vector Methods and Minimum Br...Vincenzo Russo
Clustering is an automatic learning technique aimed at grouping a set of objects into subsets or clusters. The goal is to create clusters that are coherent internally, but substantially different from each other. In plain words, objects in the same cluster should be as similar as possible, whereas objects in one cluster should be as dissimilar as possible from objects in the other clusters.
Clustering is an unsupervised learning technique, because it groups objects in clusters without any additional information: only the information provided by data is used and no human operation adds bits of information to improve the learning.
The application domains are manifold. For example, the grouping of text documents: in this case the goal is the construction of groups of documents related to each other, i.e. documents treating the same argument.
The goal of this thesis is studying in depth state-of-the-art and experimental clustering techniques. We consider two techniques. The first is known as Minimum Bregman Information principle. Such a principle generalizes the classic relocation scheme adopted yet by K-means, in order to allow the employment of a rich gamma of divergence functions said just Bregman divergences. A new, more general, clustering scheme was developed on top of this principle. Moreover, a co-clustering scheme is formulated too. This leads to an important generalization, as we will see in the sequel.
The second approach is the Support Vector Clustering. It is a clustering process which relies on the state-of-the-art of the learning machines: the Support Vector Machines. The Support Vector Clustering is currently subject of active research, as it still is in early stage of development. We have accurately analyzed such a clustering method and we have also provided some contributions which allow allow a reduction in the number of iterations and in the computational complexity and a gain in accuracy.
The main application domains we have dealt to are the text mining and the astrophysics data mining. Within these application domains we have verified and accurately analyzed the properties of both methodologies, by means of dedicated experiments.
The results are given in terms of robustness w.r.t. the missing values, the dimensionality reduction, the robustness w.r.t. the noise and the outliers, the ability of describing clusters of arbitrary shapes.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
Shadow detection and removal from single images of natural scenes is the main problem. Hence, Shadow detection and removal remained a challenging task. Significant research carried out on different shadow detection techniques. Over the last decades several approaches were introduced to deal with shadow detection and removal. Shadows are visual phenomena which happen when an area in the scene is occluded from the primary light source e.g. sun . Shadows are everywhere around us and we are rarely Confused by their presence. This article provides an overview of various methods used for shadow detection and removal using some main components like texture analysis, color information, Gaussian mixture model GMM and deterministic non model based approach. Texture Color This paper is aimed to provide a survey on various algorithms and methods of shadow detection and removal with their comparative study. Avinash Kumar Singh | Ankit Pandit ""Shadow Detection and Removal Techniques: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25201.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25201/shadow-detection-and-removal-techniques-a-perspective-view/avinash-kumar-singh
Shadow Detection and Removal in Still Images by using Hue Properties of Color...ijsrd.com
This paper involves the review of the Shadow Detection and Removal in still images. No prior information has been used such as background images etc. for finding the shadows. It is a very challenging issue for the computer vision system that shadows effect the perception of artificial intelligence based machines in appropriately detecting the particular object as shadows also picked by them and detected as false positive objects. Also in surveillance, it affects the proper tracking of humans such as at airports. We proposed a method to remove shadows which eliminates the shadow much better than existed methods. RGB space has been used of the images and some morphological operations also applied to get better results.
Visual Attention Convergence Index for Virtual Reality ExperiencesPawel Kobylinski
The paper introduces a novel quantitative method in the domain of eye tracking (ET) for virtual reality (VR). The method might be of interest to researchers on the human factor in VR, behavioral psychologists, and designers of VR experiences. Several mathematical formulas describing a novel index quantifying convergence of visual attention are introduced. The index is based on recently developed distance variance, a function of distances between observations in metric spaces. An aggregated version of the visual attention convergence index introduced in the paper allows to measure the effectiveness of any system of attentional cues employed by a designer to guide the attention of VR experience participants along an intended narration line. An individual version of the index allows to capture individual differences in the convergence of visual attention across participants. Possibilities for real-life and academic usage of the index are discussed and example results of application to real VR ET data are summarized.
Cite as:
Kobylinski P., Pochwatko G. (2020) Visual Attention Convergence Index for Virtual Reality Experiences. In: Ahram T., Taiar R., Colson S., Choplin A. (eds) Human Interaction and Emerging Technologies. IHIET 2019. Advances in Intelligent Systems and Computing, vol 1018. Springer, Cham
https://link.springer.com/chapter/10.1007/978-3-030-25629-6_48
A New Watermarking Algorithm Based on Image Scrambling and SVD in the Wavelet...IDES Editor
A new watermarking algorithm which is based on
image scrambling and SVD in the wavelet domain is discussed
in this paper. In the proposed algorithm, chaotic signals are
generated using logistic mapping and are used for scrambling
the original watermark. The initial values of logistic mapping
are taken as private keys. The covert image is decomposed
into four bands using integer wavelet transform; we apply
SVD to each band and embed the
Land Cover Feature Extraction using Hybrid Swarm Intelligence Techniques - A ...IDES Editor
The findings of recent studies are showing strong
evidence to the fact that some aspects of biogeography can be
applied to solve specific problems in science and engineering.
The proposed work presents a hybrid biologically inspired
technique that can be adapted according to the database of
expert knowledge for a more focused satellite image
classification. The paper also presents a comparative study of
our hybrid intelligent classifier with the other recent Soft
Computing Classifiers such as ACO, Hybrid Particle Swarm
Optimization-cAntMiner (PSO-ACO2), Fuzzy sets, Rough-
Fuzzy Tie up and the Semantic Web Based Classifiers and
the traditional probabilistic classifiers such as the Minimum
Distance to Mean Classifier (MDMC) and the Maximum
Likelihood Classifier (MLC).
SHARP OR BLUR: A FAST NO-REFERENCE QUALITY METRIC FOR REALISTIC PHOTOScsandit
There is an increasing demand on identifying the sharp and the blur photos from a burst of series or a mass of collection. Subjective assessment on image blurriness takes account of not only pixel variation but also the region of interest and the scene type. It makes measuring image sharpness in line with visual perception very challenging. In this paper, we devise a noreference image sharpness metric, which combines a set of gradient-based features adept in estimating Gaussian blur, out-of-focus blur and motion blur respectively. We propose a datasetadaptive logistic regression to build the metric upon multiple datasets, where over half of the samples are realistic blurry photos. Cross validation confirms that our metric outperforms thestate- of-the-art methods on the datasets with a total of 1577 images. Moreover, our metric is very fast, suitable for parallelization, and has the potential of running on mobile or embedded devices.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
Chapter provides an overview of a number of methods for visualizing tensor data. It explains principal component analysis as a technique used to process a tensor matrix and extract from it information that can directly be used in its visualization. It forms a fundamental part of many tensor data processing and visualization algorithms. Section 7.4 shows how the results of the principal component analysis can be visualized using the simple color-mapping techniques. Next parts of the chapter explain how same data can be visualized using tensor glyphs, and streamline-like visualization techniques.
In contrast to Slicer, which is a more general framework for analyzing and visualizing 3D slice-based data volumes, the Diffusion Toolkit focuses on DT-MRI datasets, and thus offers more extensive and easier to use options for fiber tracking.
Liu Natural Scene Statistics At Stereo FixationsKalle
We conducted eye tracking experiments on naturalistic stereo images presented through a haploscope, and found that fixated
luminance contrast and luminance gradient were generally higher than randomly selected luminance contrast and luminance gradient, which agrees with previous literature. However we also found that the fixated disparity contrast and disparity gradient were generally lower than randomly selected disparity contrast and disparity gradient. We discuss the implications of this remarkable
result.
Hennessey An Open Source Eye Gaze Interface Expanding The Adoption Of Eye Gaz...Kalle
There is no standard software interface in the eye-tracking industry, making it difficult for developers to integrate eye-gaze into their
applications. The combination of high cost eye-trackers and lack of applications has resulted in a slow adoption of the technology.
To expand the adoption of eye-gaze in everyday applications, we present an eye-gaze specific application programming interface that is platform and language neutral, based on open standards, easily
used and extended and free of cost.
Eye tracking scanpaths contain information about how people see, but traditional tangled, overlapping scanpath representations provide little insight about scanning strategies. The present work describes and extends several compact visual scanpath representations
that can provide additional insight about individual and aggregate/multiple scanning strategies. Three categories of representations are introduced: (1) Scaled traces are small images of scanpaths as connected saccades, allowing the comparison of relative fixation densities and distributions of saccades. (2) Time expansions, substituting ordinal position for either the scanpath’s x or y-coordinates, can uncover otherwise subtle horizontal or vertical reversals in visual scanning. (3) Radial plots represent scanpaths as a set of radial arms about an origin, with each arm representing saccade counts or lengths within a binned set of absolute or relative angles. Radial plots can convey useful shape characteristics of scanpaths, and can provide a basis for new metrics. Nine different prototype scanning strategies were represented by these plots, then heuristics were developed to classify the major strategies. The heuristics were subsequently applied to real scanpath data, to identify strategy trends. Future work will further automate the identification of scanning strategies to provide researchers with a tool to uncover and diagnosescanning-related challenges.
Eye tracking specialists often need to understand and represent aggregate scanning strategies, but methods to identify similar scanpaths and aggregate multiple scanpaths have been elusive. A
new method is proposed here to identify scanning strategies by aggregating groups of matching scanpaths automatically. A dataset of scanpaths is first converted to sequences of viewed area names, which are then represented in a dotplot. Matching sequences in the dotplot are found with linear regressions, and then used to cluster the scanpaths hierarchically. Aggregate scanning strategies are generated for each cluster and presented in an interactive dendrogram. While the clustering and aggregation method works in a bottom-up fashion, based on pair-wise matches, a top-down extension is also described, in which a scanning strategy is first input by cursor gesture, then matched against the dataset. The ability to discover both bottom-up and top-down strategy matches provides a powerful tool for scanpath analysis, and for understanding group scanning strategies.
Stellmach Advanced Gaze Visualizations For Three Dimensional Virtual Environm...Kalle
Gaze visualizations represent an effective way for gaining fast insights into eye tracking data. Current approaches do not adequately support eye tracking studies for three-dimensional (3D) virtual environments. Hence, we propose a set of advanced gaze visualization techniques for supporting gaze behavior analysis in such environments. Similar to commonly used gaze visualizations for twodimensional
stimuli (e.g., images and websites), we contribute advanced 3D scan paths and 3D attentional maps. In addition, we introduce a models of interest timeline depicting viewed models, which can be used for displaying scan paths in a selected time segment. A prototype toolkit is also discussed which combines an implementation of our proposed techniques. Their potential for facilitating eye tracking studies in virtual environments was supported by a user study among eye tracking and visualization experts.
Hussain Learning Relevant Eye Movement Feature Spaces Across UsersKalle
In this paper we predict the relevance of images based on a low-dimensional
feature space found using several users’ eye movements. Each user is given an image-based search task, during which their eye movements are extracted using a Tobii eye tracker. The users also provide us with explicit feedback regarding the relevance of images. We demonstrate that by using a greedy Nyström algorithm on the eye movement features of different users, we can find a suitable low-dimensional feature space for learning. We validate the suitability of this feature space by projecting the eye movement features of a new user into this space, training an online learning algorithm using these features, and showing that the number of mistakes (regret over time) made in predicting relevant images is lower than when using the original eye movement features. We also plot
Recall-Precision and ROC curves, and use a sign test to verify the statistical significance of our results.
Hardoon Image Ranking With Implicit Feedback From Eye MovementsKalle
In order to help users navigate an image search system, one could
provide explicit information on a small set of images as to which
of them are relevant or not to their task. These rankings are learned
in order to present a user with a new set of images that are relevant
to their task. Requiring such explicit information may not
be feasible in a number of cases, we consider the setting where
the user provides implicit feedback, eye movements, to assist when
performing such a task. This paper explores the idea of implicitly
incorporating eye movement features in an image ranking task
where only images are available during testing. Previous work had
demonstrated that combining eye movement and image features improved
on the retrieval accuracy when compared to using each of
the sources independently. Despite these encouraging results the
proposed approach is unrealistic as no eye movements will be presented
a-priori for new images (i.e. only after the ranked images are
presented would one be able to measure a user’s eye movements
on them). We propose a novel search methodology which combines
image features together with implicit feedback from users’
eye movements in a tensor ranking Support Vector Machine and
show that it is possible to extract the individual source-specific
weight vectors. Furthermore, we demonstrate that the decomposed
image weight vector is able to construct a new image-based semantic
space that outperforms the retrieval accuracy than when solely
using the image-features.
Nakayama Estimation Of Viewers Response For Contextual Understanding Of Tasks...Kalle
To estimate viewer’s contextual understanding, features of their
eye-movements while viewing question statements in response to definition statements, and features of correct and incorrect responses were extracted and compared. Twelve directional features
of eye-movements across a two-dimensional space were created, and these features were compared between correct and incorrect responses. The procedure of estimating the response was developed with Support Vector Machines, using these features. The estimation performance and accuracy were assessed across combinations of features. The number of definition statements, which needed to be memorized to answer the question statements during the experiment, affected the estimation accuracy. These results provide evidence that features of eye-movements during reading statements
can be used as an index of contextual understanding.
Integrated Hidden Markov Model and Kalman Filter for Online Object Trackingijsrd.com
Visual prior from generic real-world images study to represent that objects in a scene. The existing work presented online tracking algorithm to transfers visual prior learned offline for online object tracking. To learn complete dictionary to represent visual prior with collection of real world images. Prior knowledge of objects is generic and training image set does not contain any observation of target object. Transfer learned visual prior to construct object representation using Sparse coding and Multiscale max pooling. Linear classifier is learned online to distinguish target from background and also to identify target and background appearance variations over time. Tracking is carried out within Bayesian inference framework and learned classifier is used to construct observation model. Particle filter is used to estimate the tracking result sequentially however, unable to work efficiently in noisy scenes. Time sift variance were not appropriated to track target object with observer value to prior information of object structure. Proposal HMM based kalman filter to improve online target tracking in noisy sequential image frames. The covariance vector is measured to identify noisy scenes. Discrete time steps are evaluated for identifying target object with background separation. Experiment conducted on challenging sequences of scene. To evaluate the performance of object tracking algorithm in terms of tracking success rate, Centre location error, Number of scenes, Learning object sizes, and Latency for tracking.
2D FEATURES-BASED DETECTOR AND DESCRIPTOR SELECTION SYSTEM FOR HIERARCHICAL R...gerogepatton
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method
like ORB, SIFT or FREAK, despite being fairly slower.
2D FEATURES-BASED DETECTOR AND DESCRIPTOR SELECTION SYSTEM FOR HIERARCHICAL R...ijaia
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower
Droege Pupil Center Detection In Low Resolution ImagesKalle
In some situations, high quality eye tracking systems are not affordable. This generates the demand for inexpensive systems built upon non-specialized, off the shelf devices. Investigations show that algorithms developed for high resolution systems do not perform satisfactorily on such lowcost and low resolution systems. We investigate
algorithms specifically tailored to such low resolution input devices, based on combination of different strategies. An approach called gradient direction consensus is introduced and compared to image based correlation with adaptive templates as well as other known methods. The results are compared using synthetic input data with known ground truth.
The scanpath comparison framework based on string editing is revisited. The previous method of clustering based on k-means “preevaluation” is replaced by the mean shift algorithm followed by elliptical modeling via Principal Components Analysis. Ellipse intersection determines cluster overlap, with fast nearest-neighbor search provided by the kd-tree. Subsequent construction of Y -
matrices and parsing diagrams is fully automated, obviating prior interactive steps. Empirical validation is performed via analysis of eye movements collected during a variant of the Trail Making Test, where participants were asked to visually connect alphanumeric targets (letters and numbers). The observed repetitive position similarity index matches previously published results, providing ongoing support for the scanpath theory (at least in this situation). Task dependence of eye movements may be indicated by the global position index, which differs considerably from past results based on free viewing.
HUMAN ACTION RECOGNITION IN VIDEOS USING STABLE FEATURES sipij
Human action recognition is still a challenging problem and researchers are focusing to investigate this
problem using different techniques. We propose a robust approach for human action recognition. This is
achieved by extracting stable spatio-temporal features in terms of pairwise local binary pattern (P-LBP)
and scale invariant feature transform (SIFT). These features are used to train an MLP neural network
during the training stage, and the action classes are inferred from the test videos during the testing stage.
The proposed features well match the motion of individuals and their consistency, and accuracy is higher
using a challenging dataset. The experimental evaluation is conducted on a benchmark dataset commonly
used for human action recognition. In addition, we show that our approach outperforms individual features
i.e. considering only spatial and only temporal feature.
Improved Performance of Unsupervised Method by Renovated K-MeansIJASCSE
Clustering is a separation of data into groups of similar objects. Every group called cluster consists of objects that are similar to one another and dissimilar to objects of other groups. In this paper, the K-Means algorithm is implemented by three distance functions and to identify the optimal distance function for clustering methods. The proposed K-Means algorithm is compared with K-Means, Static Weighted K-Means (SWK-Means) and Dynamic Weighted K-Means (DWK-Means) algorithm by using Davis Bouldin index, Execution Time and Iteration count methods. Experimental results show that the proposed K-Means algorithm performed better on Iris and Wine dataset when compared with other three clustering methods.
Robust Clustering of Eye Movement Recordings for QuantiGiuseppe Fineschi
Characterizing the location and extent of a viewer’s interest, in terms of eye movement recordings, informs a range of investigations in image and scene viewing. We present an automatic data-driven method for accomplishing this, which clusters visual point-of-regard (POR) measurements into gazes and regions-ofinterest using the mean shift procedure. Clusters produced using this method form a structured representation of viewer interest, and at the same time are replicable and not heavily influenced by noise or outliers. Thus, they are useful in answering fine-grained questions about where and how a viewer examined an image.
Blur Parameter Identification using Support Vector MachineIDES Editor
This paper presents a scheme to identify the blur
parameters using support vector machine (SVM) Multiclass
approach has been used to classify the length of motion blur
and sigma parameter of atmospheric blur. Different models
of SVM have been constructed to classify the parameters.
Experimental results show the robustness of the proposed
approach to classify blur parameters.
Blignaut Visual Span And Other Parameters For The Generation Of HeatmapsKalle
Although heat maps are commonly provided by eye-tracking and visualization tools, they have some disadvantages and caution must be taken when using them to draw conclusions on eye tracking results. It is motivated here that visual span is an essential component of visualizations of eye-tracking data and an algorithm is proposed to allow the analyst to set the visual span as a parameter prior to generation of a heat map.
Although the ideas are not novel, the algorithm also indicates how transparency of the heat map can be achieved and how the color gradient can be generated to represent the probability for an object to be observed within the defined visual span. The optional addition of contour lines provides a way to visualize separate intervals in the continuous color map.
Zhang Eye Movement As An Interaction Mechanism For Relevance Feedback In A Co...Kalle
Relevance feedback (RF) mechanisms are widely adopted in Content-Based Image Retrieval (CBIR) systems to improve image retrieval performance. However, there exist some intrinsic problems: (1) the semantic gap between high-level concepts and low-level features and (2) the subjectivity of human perception of visual contents. The primary focus of this paper is to evaluate the possibility of inferring the relevance of images based on eye movement data. In total, 882 images from 101 categories are viewed by 10 subjects to test the usefulness of implicit RF, where the relevance of each image is known beforehand. A set of measures based on fixations are thoroughly evaluated which include fixation duration, fixation count, and the number of revisits. Finally, the paper proposes a decision tree to predict the user’s input during the image searching tasks. The prediction precision of the decision tree is over 87%, which spreads light on a promising integration of natural eye movement into CBIR systems in the future.
Yamamoto Development Of Eye Tracking Pen Display Based On Stereo Bright Pupil...Kalle
The intuitive user interfaces of PCs and PDAs, such as pen display and touch panel, have become widely used in recent times. In this study, we have developed an eye-tracking pen display based on the stereo bright pupil technique. First, the bright pupil camera was developed by examining the arrangement of cameras and LEDs for pen display. Next, the gaze estimation method was proposed for the stereo bright pupil camera, which enables one point calibration. Then, the prototype of the eyetracking pen display was developed. The accuracy of the system was approximately 0.7° on average, which is sufficient for human interaction support. We also developed an eye-tracking tabletop as an application of the proposed stereo bright pupil technique.
Wastlund What You See Is Where You Go Testing A Gaze Driven Power Wheelchair ...Kalle
Individuals with severe multiple disabilities have little or no opportunity to express their own wishes, make choices and move independently. Because of this, the objective of this work has been to develop a prototype for a gaze-driven device to manoeuvre powered wheelchairs or other moving platforms. The prototype has the same capabilities as a normal powered wheelchair, with two exceptions. Firstly, the prototype is controlled by eye movements instead of by a normal joystick. Secondly, the prototype is equipped with a sensor that stops all motion when the machine approaches an obstacle. The prototype has been evaluated in a preliminary clinical test with two users. Both users clearly communicated that they appreciated and had mastered the ability to control a powered wheelchair with their eye movements.
Vinnikov Contingency Evaluation Of Gaze Contingent Displays For Real Time Vis...Kalle
The visual field is the area of space that can be seen when an observer fixates a given point. Many visual capabilities vary with position in the visual field and many diseases result in changes in the visual field. With current technology, it is possible to build very complex real-time visual field simulations that employ gaze-contingent displays. Nevertheless, there are still no established techniques to evaluate such systems. We have developed a method to evaluate a system’s contingency by employing visual blind spot localization as well as foveal fixation. During the experiment, gaze-contingent and static conditions were compared. There was a strong correlation between predicted results and gaze-contingent trials. This evaluation method can also be used with patient populations and for the evaluation of gaze-contingent display systems, when there is need to evaluate a visual field outside of the foveal region.
Urbina Pies With Ey Es The Limits Of Hierarchical Pie Menus In Gaze ControlKalle
Pie menus offer several features which are advantageous especially for gaze control. Although the optimal number of slices per pie
and of depth layers has already been established for manual control, these values may differ in gaze control due to differences in spatial accuracy and congitive processing. Therefore, we investigated the layout limits for hierarchical pie menu in gaze control. Our user study indicates that providing six slices in multiple depth layers guarantees fast and accurate selections. Moreover, we compared two different methods of selecting a slice. Novices performed well with both, but selecting via selection borders produced better performance for experts than the standard dwell time selection.
Urbina Alternatives To Single Character Entry And Dwell Time Selection On Eye...Kalle
Eye typing could provide motor disabled people a reliable method of communication given that the text entry speed of current interfaces can be increased to allow for fluent communication. There are two reasons for the relatively slow text entry: dwell time selection requires waiting a certain time, and single character entry limits the maximum entry speed. We adopted a typing interface based on hierarchical pie menus, pEYEwrite [Urbina and Huckauf 2007] and included bigram text entry with one single pie iteration. Therefore, we introduced three different bigram building strategies.
Moreover, we combined dwell time selection with selection by borders, providing an alternative selection method and extra functionality. In a longitudinal study we compared participants performance during character-by-character text entry with bigram entry and with
text entry with bigrams derived by word prediction. Data showed large advantages of the new entry methods over single character text entry in speed and accuracy. Participants preferred selecting by
borders, which allowed them faster selections than the dwell time method.
Tien Measuring Situation Awareness Of Surgeons In Laparoscopic TrainingKalle
The study of surgeons’ eye movements is an innovative way of assessing skill and situation awareness, in that a comparison of eye movement strategies between expert surgeons and novices may show differences that can be used in training. Our preliminary study compared eye movements of 4 experts and
4 novices performing a simulated gall bladder removal task on a
dummy patient with an audible heartbeat and simulated vital signs displayed on a secondary monitor. We used a head-mounted Locarna PT-Mini eyetracker to record fixation locations during the operation. The results showed that novices concentrated so hard on the surgical
display that they were hardly able to look at the patient’s vital signs, even when heart rate audibly changed during the procedure. In comparison, experts glanced occasionally at the vitals monitor, thus being able to observe the patient condition.
Takemura Estimating 3 D Point Of Regard And Visualizing Gaze Trajectories Und...Kalle
The portability of an eye tracking system encourages us to develop a technique for estimating 3D point-of-regard. Unlike conventional methods, which estimate the position in the 2D image coordinates of the mounted camera, such a technique can represent richer gaze information of the human moving in the larger area. In this paper, we propose a method for estimating the 3D point-of-regard and a visualization technique of gaze trajectories under natural head movements for the head-mounted device. We employ visual SLAM technique to estimate head configuration and extract environmental information. Even in cases where the head moves dynamically, the proposed method could obtain 3D point-of-regard. Additionally, gaze trajectories are appropriately overlaid on the scene camera image.
Stevenson Eye Tracking With The Adaptive Optics Scanning Laser OphthalmoscopeKalle
Recent advances in high magnification retinal imaging have allowed for visualization of individual retinal photoreceptors, but these systems also suffer from distortions due to fixational eye motion. Algorithms developed to remove these distortions have the added benefit of providing arc second level resolution of the eye movements that produce them. The system also allows for visualization of targets on the retina, allowing for absolute retinal position measures to the level of individual cones. This paper will describe the process used to remove the eye movement artifacts and present analysis of their spectral characteristics. We find a roughly 1/f amplitude spectrum similar to that reported by Findlay (1971) with no evidence for a distinct
tremor component.
Skovsgaard Small Target Selection With Gaze AloneKalle
Accessing the smallest targets in mainstream interfaces using gaze
alone is difficult, but interface tools that effectively increase the size of selectable objects can help. In this paper, we propose a conceptual framework to organize existing tools and guide the development of new tools. We designed a discrete zoom tool and conducted a proof-of-concept experiment to test the potential of the framework and the tool. Our tool was as fast as and more accurate than the currently available two-step magnification tool. Our framework shows potential to guide the design, development, and testing of zoom tools to facilitate the accessibility of mainstream
interfaces for gaze users.
San Agustin Evaluation Of A Low Cost Open Source Gaze TrackerKalle
This paper presents a low-cost gaze tracking system that is based on a webcam mounted close to the user’s eye. The performance of the gaze tracker was evaluated in an eye-typing task using two different typing applications. Participants could type between 3.56 and 6.78 words per minute, depending on the typing system used. A pilot study to assess the usability of the system was also carried out in the home of a user with severe motor impairments. The
user successfully typed on a wall-projected interface using his eye movements.
Ryan Match Moving For Area Based Analysis Of Eye Movements In Natural TasksKalle
Analysis of recordings made by a wearable eye tracker is complicated by video stream synchronization, pupil coordinate mapping, eye movement analysis, and tracking of dynamic Areas Of Interest (AOIs) within the scene. In this paper a semi-automatic system is developed to help automate these processes. Synchronization is accomplished
via side by side video playback control. A deformable eye template and calibration dot marker allow reliable initialization via simple drag and drop as well as a user-friendly way to correct the algorithm when it fails. Specifically, drift may be corrected by nudging the detected pupil center to the appropriate coordinates. In a case study, the impact of surrogate nature views on physiological health and perceived well-being is examined via analysis of gaze over images of nature. A match-moving methodology was developed to track AOIs for this particular application but is applicable toward similar future studies.
Rosengrant Gaze Scribing In Physics Problem SolvingKalle
Eye-tracking has been widely used for research purposes in fields such as linguistics and marketing. However, there are many possibilities of how eye-trackers could be used in other disciplines like physics. A part of physics education research deals with the differences between novices and experts, specifi-cally how each group solves problems. Though there has been a great deal of research about these differences there has been no research that focuses on noticing exactly where experts and no-vices look while solving the problems. Thus, to complement the past research, I have created a new technique called gaze scrib-ing. Subjects wear a head mounted eye-tracker while solving electrical circuit problems on a graphics monitor. I monitor both scan patterns of the subjects and combine that with videotapes of their work while solving the problems. This new technique has yielded new information and elaborated on previous studies.
Qvarfordt Understanding The Benefits Of Gaze Enhanced Visual SearchKalle
In certain applications such as radiology and imagery analysis, it is important to minimize errors. In this paper we evaluate a structured inspection method that uses eye tracking information as a feedback mechanism to the image inspector. Our two-phase method starts with a free viewing phase during which gaze data is collected. During the next phase, we either segment the image, mask previously seen areas of the image, or combine the two techniques, and repeat the search. We compare the different methods
proposed for the second search phase by evaluating the inspection method using true positive and false negative rates, and subjective workload. Results show that gaze-blocked configurations reduced the subjective workload, and that gaze-blocking without segmentation showed the largest increase in true positive identifications and the largest decrease in false negative identifications of previously unseen objects.
Prats Interpretation Of Geometric Shapes An Eye Movement StudyKalle
This paper describes a study that seeks to explore the correlation between eye movements and the interpretation of geometric shapes. This study is intended to inform the development of an eye tracking interface for computational tools to support and enhance the natural interaction required in creative design. A common criticism of computational design tools is that they do not enable manipulation of designed shapes according to all perceived features. Instead the manipulations afforded are limited by formal structures of shapes. This research examines the potential for eye movement data to be used to recognise and make available for manipulation the perceived features in shapes. The objective of this study was to analyse eye movement data with the intention of recognising moments in which an interpretation of shape is made. Results suggest that fixation duration and saccade amplitude prove to be consistent indicators of shape interpretation.
Porta Ce Cursor A Contextual Eye Cursor For General Pointing In Windows Envir...Kalle
Eye gaze interaction for disabled people is often dealt with by designing ad-hoc interfaces, in which the big size of their elements compensates for both the inaccuracy of eye trackers and the instability of the human eye. Unless solutions for reliable eye cursor control are employed, gaze pointing in ordinary graphical operating environments is a very difficult task. In this paper we present an eye-driven cursor for MS Windows which behaves differently according to the “context”. When the user’s gaze is perceived within the desktop or a folder, the cursor can be discretely shifted from one icon to another. Within an application window or where there are no icons, on the contrary, the cursor can be continuously and precisely moved. Shifts in the four directions (up, down, left, right) occur through dedicated buttons. To increase user awareness of the currently pointed spot on the screen while continuously moving the cursor, a replica of the spot is provided within the active direction button, resulting in improved pointing performance.
Pontillo Semanti Code Using Content Similarity And Database Driven Matching T...Kalle
Laboratory eyetrackers, constrained to a fixed display and static (or accurately tracked) observer, facilitate automated analysis of fixation data. Development of wearable eyetrackers has extended environments and tasks that can be studied at the expense of automated analysis. Wearable eyetrackers provide 2D point-of-regard (POR) in scene-camera coordinates, but the researcher is typically interested in some high-level semantic property (e.g., object identity, region, or material) surrounding individual fixation points. The synthesis of POR into fixations and semantic information remains a labor-intensive manual task, limiting the application of wearable eyetracking.
We describe a system that segments POR videos into fixations and allows users to train a database-driven, object-recognition system. A correctly trained library results in a very accurate and semi-automated translation of raw POR data into a sequence of objects, regions or materials.
Park Quantification Of Aesthetic Viewing Using Eye Tracking Technology The In...Kalle
The purpose of this study is to explore how the viewers’ previous training is related to their aesthetic viewing in various interactions with the form and the context, in relation to apparel design. Berlyne’s two types of exploratory behavior, diversive and specific, provided a theoretical framework to this study. Twenty female subjects (mean age=21, SD=1.089) participated. Twenty model images, posed by a male and a female model, were shown on an eye-tracker screen for 10 seconds each. The findings of this study verified Berlyne’s concepts of visual exploration. One of the different findings from Berlyne’s theory was that the untrained viewers’ visual attention tended to be more significantly focused on peripheral areas of visual interest, compared to the trained viewers, while there was no significant difference on the central, foremost areas of visual interest between the two groups. The overall aesthetic viewing patterns were also identified.
Palinko Estimating Cognitive Load Using Remote Eye Tracking In A Driving Simu...Kalle
We report on the results of a study in which pairs of subjects were involved in spoken dialogues and one of the subjects also operated a simulated vehicle. We estimated the driver’s cognitive load based on pupil size measurements from a remote eye tracker. We compared the cognitive load estimates based on the physiological pupillometric data and driving performance data. The physiological and performance measures show high correspondence suggesting that remote eye tracking might provide reliable driver cognitive load estimation, especially in simulators. We also introduced a new pupillometric cognitive load measure that shows promise in tracking cognitive load changes on time scales of several seconds.
2. (a) (b)
(c) (d)
Figure 2: Collections of scanpaths of novice (a) and expert (c) pilots over a single stimulus. Time-projected scanpaths of novices (b) and of
experts (d) can be considered side views of the three-dimensional data.
ADHD through eye tracking data. They created three classifiers, scanpath s and time t, the fixation function, f (s, t), produces either
including a classifier based on Levenshtein distance, and discov- the fixation attributable at that timestamp, e.g., frame, or null (for
ered that Levenshtein’s gave the best results among their chosen saccades) from scanpath s. Figure 1 visualizes the difference be-
algorithms. To show relative improvement, we also compare the tween the standard scanpath representation and a side view of the
performance of our algorithm to a similar Levenshtein classifier. three-dimensional representation.
We extend the above definition to the function f (S, t) by chang-
3 Group-Wise Similarity ing the single scanpath parameter s to a collection of scanpaths
S. This function would then return a collection of fixations for
Our algorithm takes as input two collections of fixation-filtered all scanpaths in S at the given timestamp. Then, we may differen-
scanpaths. An example image is presented in Figure 2, displayed in tiate groups of subjects into their own scanpath sets. For instance,
2(a) with all novice scanpaths and in 2(c) with all expert scanpaths. in our experiment, we study the differences between experts and
From a simple visual examination, there is no obvious characteris- novices. We may then create an expert scanpath set E and a novice
tic that stands out for either collection. A procedure is then needed scanpath set N . The functions f (E, t) and f (N, t) would then re-
to perform a deeper statistical analysis of each collection. turn collections of fixations at timestamp t for experts and novices,
The original impetus for this approach was the desire to formulate respectively (Figures 2(b) and 2(d) visualize the same data as in
an elegant scanpath comparison measure for dynamic stimuli, such Figures 2(a) and 2(c), but as side views of their three-dimensional
as movies or interactive tasks. Current string-editing approaches representations).
are not sufficient for video. For example, a string-editing alignment
could mistakenly align AOIs from frames that are many seconds These group-specific collections of fixations for single frames may
apart. There is nothing to explicitly constrain AOIs to only coincide be clustered by the mean shift approach described by Santella and
within specific temporal limits. DeCarlo [2004]. The resulting clusters serve as general AOIs for a
given frame, describing regions of varying interest for that specific
From the perspective of a collection of movie frames, each frame group of individuals. We may then construct a probabilistic model
can be thought of as a separate stimulus. The scanpath for a sin- of expected attention for that group. Such a model for a single
gle subject, viewing a movie stimulus, can then be broken up into frame is visualized in Figure 3.
a collection of fixation-frame units, which are more or less inde-
pendent from each other. This conceptualization of a scanpath dif- Each frame will have a separate model associated with it, and we
fers from the conventional view, in that the conventional visualiza- may calculate the “error per group” of a given fixation in a frame by
tion is a “projection” of fixations over time onto a two-dimensional calculating the summation of the Gaussian distances from the fixa-
plane. Our conceptualization avoids this projection entirely. Thus, tion point to all group-specific cluster centers. We use a Gaussian
we produce a three-dimensional “scanpath function”. Given some kernel with standard deviation of 50 pixels to determine the dis-
102
3. this approach to validate whether our group-wise similarity mea-
sure produces information that may be used to reliably discriminate
between groups. A classifier must be constructed for each group,
e.g., the expert group and the novice group. The classifier for expert
data will be described below. The classifier for novice data may be
constructed identically, though with different input values.
As input to our classifier, we provide a list of group-wise similarity
scores, corresponding to the similarities of individual scanpaths to
the expert model, as described above. The goal of the expert clas-
sifier, then, is to determine some similarity threshold score, above
which indicates that a given scanpath is likely to be expert and be-
low which indicates that the scanpath is unlikely to be expert.
We use the receiver operating characteristic (ROC) curve to find
Figure 3: Mixture of Gaussians for expert fixations at a discrete this threshold. A thorough description of the curve may be found in
timestamp. Displayed novice fixations were not used in the clus- Fogarty et al. [2005]. This curve may also be used to compute the
tering operation. Note that the fixation labeled ‘A’ is far from the area under the ROC curve (AUC). This value describes the discrim-
cluster centers, and thus has lower similarity than fixation labeled inative ability of a classifier. Simple percentage accuracy values
‘B’ that is close to a cluster center. may be misrepresentative, especially in skewed cases, such as hav-
ing a large quantity of data from one class and a small quantity of
data from another. The AUC value describes the probability that an
tance value, which we then invert. Thus, a fixation point collocated individual instance of one class will be classified differently from
with a cluster mean or centroid has inverse distance value (similar- an instance of another class.
ity) of 1.0, and a fixation point more than 50 pixels away from the
cluster mean has inverse distance value close to 0. The summation Two classifiers are being trained: an expert and a novice classifier.
of the cluster similarities for a single fixation point are divided by This means that two scores are produced for a single instance. Each
the number of clusters, giving a value between 0 and 1. score describes the probability that an instance is a member of the
expert or novice group, respectively. In order to decide which class
With a mechanism to evaluate group-specific error, or rather simi- this instance conclusively belongs to, we use a heuristic. There
larity, of fixation points in individual frames, we may then extrap- are a few possibilities for the arrangement of these scores. First,
olate this process over the entire scanpath duration by summing in- the expert score may be higher than the expert threshold, and the
dividual similarities for each frame and then returning the average. novice score may be lower than the novice threshold. This case
Thus, a scanpath in which most fixation points lie near to group- is trivially expert. Similarly, an instance with expert score lower
specific clusters will have similarity close to 1.0 for that group, than the expert threshold and novice score higher than the novice
while a scanpath in which most fixations points lie far away from threshold is trivially novice. In the case of both scores being above
those clusters will have similarity close to 0. This metric may then or below their respective thresholds, we divide the score of each
be extrapolated further to describe the similarity of one group of classifier by its threshold value and choose the greater of the two.
scanpaths to another by simply averaging together the group-wise
similarities for each scanpath in one group to the entire other group.
5 Results
The data collected for expert/novice classification purposes did not,
in fact, use video as stimulus. Nevertheless, while the video-based
In order to evaluate our method we analyzed the results of a study
approach is expected to be more reliable for video, its application
wherein 20 high-time pilots (experts) and 20 non-pilots (novices)
to static images would also be beneficial. In concordance with the
were presented with 20 different images of weather. Subjects
video paradigm, we take samples from our data every 16 millisec-
were asked to determine whether they would continue their current
onds. Thus, this procedure may be utilized for analysis over both
flight path or if they needed to divert. Their eye movements were
static and dynamic stimuli. In our study, recorded scanpaths are of
recorded by a Tobii ET-1750 eye tracker (their verbal responses
various lengths. We must, therefore, specify a time window over
were ignored in our analysis). Our objective was to produce a clas-
which to collect fixation data. The upper bound on the length of
sifier that can predict whether a subject is expert or novice, based
this window is the shorter of either the length of the scanpath being
solely on their eye movements.
compared or the mean of the scanpath lengths for a given stimulus.
To evaluate the capabilities of this new approach, we compared the With two classes, a random classifier would be expected to produce
results to a group-wise extension of pairwise string-editing similar- 0.50 accuracy and AUC values. Evaluation metrics for our mech-
ity. The group-wise string-editing similarity of a single scanpath anism are listed in Table 1. In our evaluation, we refer to expert
to a group of scanpaths is the average pairwise similarity of that data as our positive class and novice data as negative. According to
scanpath to each scanpath in the group it is being compared to. the p-values, all metrics are significantly higher than random for our
method, while only the accuracy and AUC for the positive classifier
are significantly higher for the string-editing method.
4 Classification
Results show the classifier’s discriminative ability over a single
Our method of group-wise scanpath similarity is validated by a stimulus. Given multiple stimuli, our measure is extrapolated over
machine learning validation approach. Machine learning, specifi- all stimuli for each subject. A “majority vote” is then used, where
cally classification, is a statistical framework which takes, as input, one vote is drawn from each stimulus. If more than half the votes
one or more groups of data and produces, as output, probability indicate that a subject is expert, that subject is then classified as
values that describe the likelihood that some arbitrary datum is a conclusively expert. Otherwise, a subject is classified as novice.
member of one or more of the defined groups. Thus, we may use Accuracies for this voting mechanism are listed in Table 2.
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4. Cross-Validation Results those scanpaths. This mechanism has been empirically and statis-
posAcc negAcc totAcc posAUC negAUC tically validated, showing that it is capable of discriminating be-
Temporal tween groupings at least as diverse as expert/novice subject appel-
Average 0.71 0.64 0.68 0.85 0.86 lation, with greater accuracy and reliability than random. Potential
Std Dev 0.07 0.12 0.07 0.07 0.04 applications include training environments, neurological disorder
Median 0.74 0.66 0.68 0.87 0.86 diagnosis, and, in general, evaluation of attention deviation from
p-value 0.00 0.01 0.00 0.00 0.00 that expected or desired during a dynamic stimulus. Future work
String-editing may include pre-alignment of unclassified scanpaths with classified
Average 0.49 0.64 0.57 0.81 0.72 scanpaths, attempting to increase the accuracy further during the
Std Dev 0.17 0.13 0.06 0.06 0.11 calculation of class similarity.
Median 0.48 0.64 0.57 0.82 0.71
p-value 0.98 0.02 0.16 0.00 0.00
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