PTSA Coffee with Administration Slide Presentation (8/20/15)pudongptsa
Meeting presentation including introduction by administration, PTSA organizational structure, executive committee, divisional teams and committee chairs, upcoming events
Toward Accurate and Robust Cross-Ratio based Gaze Trackers Through Learning F...Jia-Bin Huang
Jia-Bin Huang, Qin Cai, Zicheng Liu, Narendra Ahuja, and Zhengyou Zhang
Towards Accurate and Robust Cross-Ratio based Gaze Trackers Through Learning From Simulation
Proceedings of ACM Symposium on Eye Tracking Research & Applications (ETRA), 2014
ETRA 2014 Best Paper Award
In this paper, we describe a new interactive image completion system that allows users to easily specify various forms of mid-level structures in the image. Our system supports the specification of four basic symmetric types: reflection, translation, rotation, and glide. The user inputs are automatically converted into guidance maps that encode
possible candidate shifts and, indirectly, local transformations of rotation and scale. These guidance maps are used in conjunction with a color matching cost for image
completion. We show that our system is capable of handling a variety of challenging examples.
http://www.jiabinhuang.com/
Saliency Detection via Divergence Analysis: A Unified Perspective ICPR 2012Jia-Bin Huang
A number of bottom-up saliency detection algorithms have been proposed in the literature. Since these have been developed from intuition and principles inspired by psychophysical studies of human vision, the theoretical relations among them are unclear. In this paper, we present a unifying perspective. Saliency of an image area is defined in terms of divergence between certain feature distributions estimated from the
central part and its surround. We show that various, seemingly different saliency estimation algorithms are in fact closely related. We also discuss some commonly
used center-surround selection strategies. Experiments with two datasets are presented to quantify the relative advantages of these algorithms.
Best student paper award in Computer Vision and Robotics Track
PTSA Coffee with Administration Slide Presentation (8/20/15)pudongptsa
Meeting presentation including introduction by administration, PTSA organizational structure, executive committee, divisional teams and committee chairs, upcoming events
Toward Accurate and Robust Cross-Ratio based Gaze Trackers Through Learning F...Jia-Bin Huang
Jia-Bin Huang, Qin Cai, Zicheng Liu, Narendra Ahuja, and Zhengyou Zhang
Towards Accurate and Robust Cross-Ratio based Gaze Trackers Through Learning From Simulation
Proceedings of ACM Symposium on Eye Tracking Research & Applications (ETRA), 2014
ETRA 2014 Best Paper Award
In this paper, we describe a new interactive image completion system that allows users to easily specify various forms of mid-level structures in the image. Our system supports the specification of four basic symmetric types: reflection, translation, rotation, and glide. The user inputs are automatically converted into guidance maps that encode
possible candidate shifts and, indirectly, local transformations of rotation and scale. These guidance maps are used in conjunction with a color matching cost for image
completion. We show that our system is capable of handling a variety of challenging examples.
http://www.jiabinhuang.com/
Saliency Detection via Divergence Analysis: A Unified Perspective ICPR 2012Jia-Bin Huang
A number of bottom-up saliency detection algorithms have been proposed in the literature. Since these have been developed from intuition and principles inspired by psychophysical studies of human vision, the theoretical relations among them are unclear. In this paper, we present a unifying perspective. Saliency of an image area is defined in terms of divergence between certain feature distributions estimated from the
central part and its surround. We show that various, seemingly different saliency estimation algorithms are in fact closely related. We also discuss some commonly
used center-surround selection strategies. Experiments with two datasets are presented to quantify the relative advantages of these algorithms.
Best student paper award in Computer Vision and Robotics Track
Enhancing Color Representation for the Color Vision Impaired (CVAVI 2008)Jia-Bin Huang
In this paper, we propose a fast re-coloring algorithm to improve the accessibility for the color vision impaired. Compared to people with normal color vision, people with color vision impairment have difficulty in distinguishing between certain combinations of colors. This may hinder visual communication owing to the increasing use of colors in recent years. To address this problem, we re-map the hue components in the HSV color space based on the statistics of local characteristics of the original color image. We enhance the color contrast through generalized histogram equalization. A control parameter is provided for various users to specify the degree of enhancement to meet their needs. Experimental results are illustrated to demonstrate the effectiveness and efficiency of the proposed re-coloring algorithm.
Reading academic papers is one of the most important parts of scientific research. However, junior graduate students may spend a lot of time learning how to read papers efficiently and effectively. In this talk, I will discuss some basic issues and introduce useful websites/tools/tips for paper reading.
Image Completion using Planar Structure Guidance (SIGGRAPH 2014)Jia-Bin Huang
We propose a method for automatically guiding patch-based image completion using mid-level structural cues. Our method first estimates planar projection parameters, softly segments the known region into planes, and discovers translational regularity within these planes. This information is then converted into soft constraints for the low-level completion algorithm by defining prior probabilities for patch offsets and transformations. Our method handles multiple planes, and in the absence of any detected planes falls back to a baseline fronto-parallel image completion algorithm. We validate our technique through extensive comparisons with state-of-the-art algorithms on a variety of scenes.
Project page: https://sites.google.com/site/jbhuang0604/publications/struct_completion
Single Image Super-Resolution from Transformed Self-Exemplars (CVPR 2015)Jia-Bin Huang
Self-similarity based super-resolution (SR) algorithms are able to produce visually pleasing results without extensive training on external databases. Such algorithms exploit the statistical prior that patches in a natural image tend to recur within and across scales of the same image. However, the internal dictionary obtained from the given image may not always be sufficiently expressive to cover the textural appearance variations in the scene. In this paper, we extend self-similarity based SR to overcome this drawback. We expand the internal patch search space by allowing geometric variations. We do so by explicitly localizing planes in the scene and using the detected perspective geometry to guide the patch search process. We also incorporate additional affine transformations to accommodate local shape variations. We propose a compositional model to simultaneously handle both types of transformations. We extensively evaluate the performance in both urban and natural scenes. Even without using any external training databases, we achieve significantly superior results on urban scenes, while maintaining comparable performance on natural scenes as other state-of-the-art SR algorithms.
http://bit.ly/selfexemplarsr
Estimating Human Pose from Occluded Images (ACCV 2009)Jia-Bin Huang
We address the problem of recovering 3D human pose from single 2D images, in which the pose estimation problem is formulated as a direct nonlinear regression from image observation to 3D joint positions. One key issue that has not been addressed in the literature is how to estimate 3D pose when humans in the scenes are partially or heavily occluded. When occlusions occur, features extracted from image observations (e.g., silhouettes-based shape features, histogram of oriented gradient, etc.) are seriously corrupted, and consequently the regressor (trained on un-occluded images) is unable to estimate pose states correctly. In this paper, we present a method that is capable of handling occlusions using sparse signal representations, in which each test sample is represented as a compact linear combination of training samples. The sparsest solution can then be efficiently obtained by solving a convex optimization problem with certain norms (such as l1-norm). The corrupted test image can be recovered with a sparse linear combination of un-occluded training images which can then be used for estimating human pose correctly (as if no occlusions exist). We also show that the proposed approach implicitly performs relevant feature selection with un-occluded test images. Experimental results on synthetic and real data sets bear out our theory that with sparse representation 3D human pose can be robustly estimated when humans are partially or heavily occluded in the scenes.
Computer vision techniques can be seen in various aspects in our daily life with tremendous impacts. This slides aim at introducing basic concepts of computer vision and applications for the general public.
Download link: https://uofi.box.com/shared/static/24vy7aule67o4g6djr83hzurf5a9lfp6.pptx
General principles and tricks for writing fast MATLAB code.
Powerpoint slides: https://uofi.box.com/shared/static/yg4ry6s1c9qamsvk6sk7cdbzbmn2z7b8.pptx
Research 101 - Paper Writing with LaTeXJia-Bin Huang
Paper Writing with LaTeX
PDF: https://filebox.ece.vt.edu/~jbhuang/slides/Research%20101%20-%20Paper%20Writing%20with%20LaTeX.pdf
PPTX: https://filebox.ece.vt.edu/~jbhuang/slides/Research%20101%20-%20Paper%20Writing%20with%20LaTeX.pptx
The first part of this course is designed to be an introduction to the rest of the week. It will give some information about me (Dr. David Westerman, presenter for this week's MOOC), some ideas about expectations, etc. and also introduce a news story that we will use as a thread throughout the rest of the week.
Join the conversation at www.wvucommmooc.org.
Here is my updated CV using the ModernCV template (http://www.latextemplates.com/template/moderncv-cv-and-cover-letter).
You can find the Tex source file in (https://dl.dropbox.com/u/2810224/Homepage/resume/modern%20style.rar)
Estimating Human Pose from Occluded Images (ACCV 2009)Jia-Bin Huang
We address the problem of recovering 3D human pose from single 2D images, in which the pose estimation problem is formulated as a direct nonlinear regression from image observation to 3D joint positions. One key issue that has not been addressed in the literature is how to estimate 3D pose when humans in the scenes are partially or heavily occluded. When occlusions occur, features extracted from image observations (e.g., silhouettes-based shape features, histogram of oriented gradient, etc.) are seriously corrupted, and consequently the regressor (trained on un-occluded images) is unable to estimate pose states correctly. In this paper, we present a method that is capable of handling occlusions using sparse signal representations, in which each test sample is represented as a compact linear combination of training samples. The sparsest solution can then be efficiently obtained by solving a convex optimization problem with certain norms (such as l1-norm). The corrupted test image can be recovered with a sparse linear combination of un-occluded training images which can then be used for estimating human pose correctly (as if no occlusions exist). We also show that the proposed approach implicitly performs relevant feature selection with un-occluded test images. Experimental results on synthetic and real data sets bear out our theory that with sparse representation 3D human pose can be robustly estimated when humans are partially or heavily occluded in the scenes.
18. GENERAL
INFORMATION
Time
• Wednesday
• 8:00 PM – 11:00 PM
• Saturday
• 4:00 PM – 7:00 PM
Place
• Activities and Recreation Center (ARC) <= mostly likely here
• Campus Recreation Center East (CRCE)
• Depend on the availability of the courts
Spontaneous Play:
• Whenever you want!
19. MORE INFORMATION
Facebook group
• https://www.facebook.com/FVEUIUC
• https://www.facebook.com/groups/139031272818595/
Tentative events
• Midwest Taiwanese student tournament – September
• Friendly game with Purdue – Mid October
• St Louis Volleyball tournament – Late October
• UIUC Intramural – Late November
• And many other activities!
Contact:
• Jia-Bin Huang: jbhuang0604@gmail.com
• Michelle Lin: michelle16845@yahoo.com.tw