The document discusses opportunities and challenges in video search. It begins with an introduction to video search and outlines key market trends driving growth in online video. It then explores opportunities in leveraging metadata, community contributions, and large datasets. However, it also notes challenges including developing theoretical frameworks for video search and addressing the complexity of video content analysis.
Multimedia content based retrieval slideshare.pptgovintech1
information retrieval for text and multimedia content has become an important research area.
Content based retrieval in multimedia is a challenging problem since multimedia data needs detailed interpretation
from pixel values. In this presentation, an overview of the content based retrieval is presented along with
the different strategies in terms of syntactic and semantic indexing for retrieval. The matching techniques
used and learning methods employed are also analyzed.
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.
Multimedia Semantics:Metadata, Analysis and InteractionRaphael Troncy
Multimedia Semantics:Metadata, Analysis and Interaction. Keynote Talk at the Latin-American Conference on Networked Electronic Media (LACNEM), August 2009, Bogota, Colombia
BUILDING A SCALABLE MULTIMEDIA WEB OBSERVATORYJonathon Hare
Web and Internet Science research group seminar series. University of Southampton. 13th March 2013.
The web is inherently multimedia in nature, and contains data and information in many different audio, visual and textual forms. To fully understand the nature of the web and the information contained within it, it is necessary to harness all modalities of data. Within the EU funded ARCOMEM project, we are building a platform for crawling and analysing samples of web and social-web data at scale. Whilst the project is ostensibly about issues related to intelligent web-archiving, the ARCOMEM software has features that make it ideal for use as a platform for a scalable Multimedia Web Observatory.
This talk will describe the ARCOMEM approach from data harvesting through to detailed content analysis and demonstrate how this approach relates to a multimedia web observatory. In addition to describing the overall framework, I'll show some of the research aspects of the system related specifically to multimodal multimedia data in small (>100GB) to medium-scale (multi-terabyte) web archives, and demonstrate how these are targeted to our Parliamentarian and Journalist end-users.
Multimedia content based retrieval slideshare.pptgovintech1
information retrieval for text and multimedia content has become an important research area.
Content based retrieval in multimedia is a challenging problem since multimedia data needs detailed interpretation
from pixel values. In this presentation, an overview of the content based retrieval is presented along with
the different strategies in terms of syntactic and semantic indexing for retrieval. The matching techniques
used and learning methods employed are also analyzed.
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.
Multimedia Semantics:Metadata, Analysis and InteractionRaphael Troncy
Multimedia Semantics:Metadata, Analysis and Interaction. Keynote Talk at the Latin-American Conference on Networked Electronic Media (LACNEM), August 2009, Bogota, Colombia
BUILDING A SCALABLE MULTIMEDIA WEB OBSERVATORYJonathon Hare
Web and Internet Science research group seminar series. University of Southampton. 13th March 2013.
The web is inherently multimedia in nature, and contains data and information in many different audio, visual and textual forms. To fully understand the nature of the web and the information contained within it, it is necessary to harness all modalities of data. Within the EU funded ARCOMEM project, we are building a platform for crawling and analysing samples of web and social-web data at scale. Whilst the project is ostensibly about issues related to intelligent web-archiving, the ARCOMEM software has features that make it ideal for use as a platform for a scalable Multimedia Web Observatory.
This talk will describe the ARCOMEM approach from data harvesting through to detailed content analysis and demonstrate how this approach relates to a multimedia web observatory. In addition to describing the overall framework, I'll show some of the research aspects of the system related specifically to multimodal multimedia data in small (>100GB) to medium-scale (multi-terabyte) web archives, and demonstrate how these are targeted to our Parliamentarian and Journalist end-users.
Semantics In Digital Photos A Contenxtual AnalysisAllenWu
Interpreting the semantics of an image is a hard problem. However, for storing and indexing large multimedia collections,
it is essential to build systems that can automatically extract semantics from images. In this research we show how we can fuse content and context to extract semantics from digital photographs. Our experiments show that if we can properly model context associated with media, we can interpret semantics using only a part of high dimensional content data.
OpenIMAJ and ImageTerrier: Java Libraries and Tools for Scalable Multimedia A...Jonathon Hare
ACM Multimedia 2011, Scottsdale, Arizona, USA, 28 Nov - 01 Dec 2011.
http://eprints.soton.ac.uk/273040/
OpenIMAJ and ImageTerrier are recently released open- source libraries and tools for experimentation and devel- opment of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries con- tain methods for processing images and extracting state- of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and process- ing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering al- gorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenI- MAJ also incorporates a number of tools to enable extremely- large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test- bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures.
Towards Collaborative Annotation for Video AccessibilityRaphael Troncy
Towards Collaborative Annotation for Video Accessibility - Talk given at the 7th International Cross-Disciplinary Conference on Web Accessibility (W4A'2010), Raleigh (NC), USA, April 29th 2010
Chcete vědět víc? Mnoho dalších prezentací, videí z konferencí, fotografií i jiných dokumentů je k dispozici v institucionálním repozitáři NTK: http://repozitar.techlib.cz
Would you like to know more? Find presentations, reports, conference videos, photos and much more in our institutional repository at: http://repozitar.techlib.cz/?ln=en
Multimodal Searching and Semantic Spaces: ...or how to find images of Dalmati...Jonathon Hare
Tutorial at the "Reality of the Semantic Gap in Image Retrieval" tutorial at the first international conference on Semantics And digital Media Technology (SAMT 2006). 6th December 2006.
SP1: Exploratory Network Analysis with GephiJohn Breslin
ICWSM 2011 Tutorial
Sebastien Heymann and Julian Bilcke
Gephi is an interactive visualization and exploration software for all kinds of networks and relational data: online social networks, emails, communication and financial networks, but also semantic networks, inter-organizational networks and more. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Users interact with the visualization and manipulate structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypotheses, intuitively discover patterns or errors in large data collections.
In this tutorial we will provide a hands-on demonstration of the essential functionalities of Gephi, based on a real case scenario: the exploration of student networks from the "Facebook100" dataset (Social Structure of Facebook Networks, Amanda L. Traud et al, 2011). The participants will be guided step by step through the complete chain of representation, manipulation, layout, analysis and aesthetics refinements. Particular focus will be put on filters and metrics for the creation of their first visualizations. They will be incited to compare the hypotheses suggested by their own exploration to the results actually published in the academic paper afterwards. They finally will walk away with the practical knowledge enabling them to use Gephi for their own projects. The tutorial is intended for professionals, researchers and graduates who wish to learn how playing during a network exploration can speed up their studies.
Sébastien Heymann is a Ph.D. Candidate in Computer Science at Université Pierre et Marie Curie, France. His research at the ComplexNetworks team focuses on the dynamics of realworld networks. He leads the Gephi project since 2008, and is the administrator of the Gephi Consortium.
Julian Bilcke is a Software Engineer at ISC-PIF (Complex Systems Institute of Paris, France). He is a founder and a developer for the Gephi project since 2008.
Millions of active users all around the world are using online social network such as Facebook, Twitter, Tumblr and
LinkedIn. Most of the social networks have weak user to user authentication method, which is based on some basic information like
name, images etc. These weaknesses make it easier to misuse user’s information and do identity cloning attack to form fake profile.
This paper presents a classification and analysis of a detection mechanisms of clone attacks on social network, based on attribute
similarity, friend network similarity, and profile analysis for a time interval and record of Internet Protocol sequences. In this project we
have proposed discrete wavelet transform algorithm for data hiding. For watermarking technique Java static watermarking systems and
algorithms is been used.
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
Here are Important things about Image and Video Annotation that you should know for machine learning and to make your annotation project well & good your vision our thoughts.
An overview of Media Analytics outlining the evolution of image classification and knowledge extraction. The presentation offers an insight into the Big-Data Analytics for Media Management.
Abstract: The main communication methods used by deaf people are sign language, but opposed to common thought, there is no specific universal sign language: every country or even regional group uses its own set of signs. The use of sign language in digital systems can enhance communication in both directions: animated avatars can synthesize signals based on voice or text recognition; and sign language can be translated into various text or sound forms based on different images, videos and sensors input. The ultimate goal of this research, but it is not a simple spelling of spoken language, so that recognizing different signs or letters of the alphabet (which has been a common approach) is not sufficient for its transcription and automatic interpretation. Here proposes an algorithm and method for an application this would help us in recognising the various user defined signs. The palm images of right and left hand are loaded at runtime. Firstly these images will be seized and stored in directory. Then technique called Template matching is used for finding areas of an image that match (are similar) to a template image (patch). Our goal is to detect the highest matching area. We need two primary components- A) Source image (I): In the template image in which we try to find a match. B) Template image (T): The patch image which will be compared to the template image. In proposed system user defined patterns will be having 60% accuracy while default patterns will be provided with 80% accuracy.
https://telecombcn-dl.github.io/2017-dlsl/
Winter School on Deep Learning for Speech and Language. UPC BarcelonaTech ETSETB TelecomBCN.
The aim of this course is to train students in methods of deep learning for speech and language. Recurrent Neural Networks (RNN) will be presented and analyzed in detail to understand the potential of these state of the art tools for time series processing. Engineering tips and scalability issues will be addressed to solve tasks such as machine translation, speech recognition, speech synthesis or question answering. Hands-on sessions will provide development skills so that attendees can become competent in contemporary data analytics tools.
Calgary Multimedia Company consist of media and information that makes use of wide range of diverse content types. It is the adjustment with media that utilizes computer to show such as text-only or traditional types of printed or hand-produced material. Multimedia take account of an arrangement of content, aCalgary Multimedia Companyudio, still images, moving picture, video or interactivity text forms.
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...maranlar
Within computer science, "Multimedia" is a field of research that investigates how computers can support people in communication, information finding, and knowledge/opinion building. Multimedia content is defined broadly. It includes not only video, but also images accompanied by text and other information (for example, a geo-location). It can be professionally produced, or generated by users for online sharing. Computer scientists historically have a “love-hate” relationship with multimedia. They “love” it because of the richness of the data sources and the wealth of available data, which leads to interesting problems to tackle with machine learning. They “hate” it because multimedia is a diffuse and moving target: the interpretation of multimedia differs from person to person, and changes over time in the course of its use as a communication medium. This talk gives a view onto ongoing research in the area of multimedia information retrieval algorithms, which help people find multimedia. We look at a series of topics that reveal how pattern recognition, text processing, and crowdsourcing tools are used in multimedia research, and discuss both their limitations and their potential.
Semantics In Digital Photos A Contenxtual AnalysisAllenWu
Interpreting the semantics of an image is a hard problem. However, for storing and indexing large multimedia collections,
it is essential to build systems that can automatically extract semantics from images. In this research we show how we can fuse content and context to extract semantics from digital photographs. Our experiments show that if we can properly model context associated with media, we can interpret semantics using only a part of high dimensional content data.
OpenIMAJ and ImageTerrier: Java Libraries and Tools for Scalable Multimedia A...Jonathon Hare
ACM Multimedia 2011, Scottsdale, Arizona, USA, 28 Nov - 01 Dec 2011.
http://eprints.soton.ac.uk/273040/
OpenIMAJ and ImageTerrier are recently released open- source libraries and tools for experimentation and devel- opment of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries con- tain methods for processing images and extracting state- of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and process- ing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering al- gorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenI- MAJ also incorporates a number of tools to enable extremely- large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test- bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures.
Towards Collaborative Annotation for Video AccessibilityRaphael Troncy
Towards Collaborative Annotation for Video Accessibility - Talk given at the 7th International Cross-Disciplinary Conference on Web Accessibility (W4A'2010), Raleigh (NC), USA, April 29th 2010
Chcete vědět víc? Mnoho dalších prezentací, videí z konferencí, fotografií i jiných dokumentů je k dispozici v institucionálním repozitáři NTK: http://repozitar.techlib.cz
Would you like to know more? Find presentations, reports, conference videos, photos and much more in our institutional repository at: http://repozitar.techlib.cz/?ln=en
Multimodal Searching and Semantic Spaces: ...or how to find images of Dalmati...Jonathon Hare
Tutorial at the "Reality of the Semantic Gap in Image Retrieval" tutorial at the first international conference on Semantics And digital Media Technology (SAMT 2006). 6th December 2006.
SP1: Exploratory Network Analysis with GephiJohn Breslin
ICWSM 2011 Tutorial
Sebastien Heymann and Julian Bilcke
Gephi is an interactive visualization and exploration software for all kinds of networks and relational data: online social networks, emails, communication and financial networks, but also semantic networks, inter-organizational networks and more. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Users interact with the visualization and manipulate structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypotheses, intuitively discover patterns or errors in large data collections.
In this tutorial we will provide a hands-on demonstration of the essential functionalities of Gephi, based on a real case scenario: the exploration of student networks from the "Facebook100" dataset (Social Structure of Facebook Networks, Amanda L. Traud et al, 2011). The participants will be guided step by step through the complete chain of representation, manipulation, layout, analysis and aesthetics refinements. Particular focus will be put on filters and metrics for the creation of their first visualizations. They will be incited to compare the hypotheses suggested by their own exploration to the results actually published in the academic paper afterwards. They finally will walk away with the practical knowledge enabling them to use Gephi for their own projects. The tutorial is intended for professionals, researchers and graduates who wish to learn how playing during a network exploration can speed up their studies.
Sébastien Heymann is a Ph.D. Candidate in Computer Science at Université Pierre et Marie Curie, France. His research at the ComplexNetworks team focuses on the dynamics of realworld networks. He leads the Gephi project since 2008, and is the administrator of the Gephi Consortium.
Julian Bilcke is a Software Engineer at ISC-PIF (Complex Systems Institute of Paris, France). He is a founder and a developer for the Gephi project since 2008.
Millions of active users all around the world are using online social network such as Facebook, Twitter, Tumblr and
LinkedIn. Most of the social networks have weak user to user authentication method, which is based on some basic information like
name, images etc. These weaknesses make it easier to misuse user’s information and do identity cloning attack to form fake profile.
This paper presents a classification and analysis of a detection mechanisms of clone attacks on social network, based on attribute
similarity, friend network similarity, and profile analysis for a time interval and record of Internet Protocol sequences. In this project we
have proposed discrete wavelet transform algorithm for data hiding. For watermarking technique Java static watermarking systems and
algorithms is been used.
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
Here are Important things about Image and Video Annotation that you should know for machine learning and to make your annotation project well & good your vision our thoughts.
An overview of Media Analytics outlining the evolution of image classification and knowledge extraction. The presentation offers an insight into the Big-Data Analytics for Media Management.
Abstract: The main communication methods used by deaf people are sign language, but opposed to common thought, there is no specific universal sign language: every country or even regional group uses its own set of signs. The use of sign language in digital systems can enhance communication in both directions: animated avatars can synthesize signals based on voice or text recognition; and sign language can be translated into various text or sound forms based on different images, videos and sensors input. The ultimate goal of this research, but it is not a simple spelling of spoken language, so that recognizing different signs or letters of the alphabet (which has been a common approach) is not sufficient for its transcription and automatic interpretation. Here proposes an algorithm and method for an application this would help us in recognising the various user defined signs. The palm images of right and left hand are loaded at runtime. Firstly these images will be seized and stored in directory. Then technique called Template matching is used for finding areas of an image that match (are similar) to a template image (patch). Our goal is to detect the highest matching area. We need two primary components- A) Source image (I): In the template image in which we try to find a match. B) Template image (T): The patch image which will be compared to the template image. In proposed system user defined patterns will be having 60% accuracy while default patterns will be provided with 80% accuracy.
https://telecombcn-dl.github.io/2017-dlsl/
Winter School on Deep Learning for Speech and Language. UPC BarcelonaTech ETSETB TelecomBCN.
The aim of this course is to train students in methods of deep learning for speech and language. Recurrent Neural Networks (RNN) will be presented and analyzed in detail to understand the potential of these state of the art tools for time series processing. Engineering tips and scalability issues will be addressed to solve tasks such as machine translation, speech recognition, speech synthesis or question answering. Hands-on sessions will provide development skills so that attendees can become competent in contemporary data analytics tools.
Calgary Multimedia Company consist of media and information that makes use of wide range of diverse content types. It is the adjustment with media that utilizes computer to show such as text-only or traditional types of printed or hand-produced material. Multimedia take account of an arrangement of content, aCalgary Multimedia Companyudio, still images, moving picture, video or interactivity text forms.
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...maranlar
Within computer science, "Multimedia" is a field of research that investigates how computers can support people in communication, information finding, and knowledge/opinion building. Multimedia content is defined broadly. It includes not only video, but also images accompanied by text and other information (for example, a geo-location). It can be professionally produced, or generated by users for online sharing. Computer scientists historically have a “love-hate” relationship with multimedia. They “love” it because of the richness of the data sources and the wealth of available data, which leads to interesting problems to tackle with machine learning. They “hate” it because multimedia is a diffuse and moving target: the interpretation of multimedia differs from person to person, and changes over time in the course of its use as a communication medium. This talk gives a view onto ongoing research in the area of multimedia information retrieval algorithms, which help people find multimedia. We look at a series of topics that reveal how pattern recognition, text processing, and crowdsourcing tools are used in multimedia research, and discuss both their limitations and their potential.
Presentation for our multimedia information management project. We developed a multi modal search engine that uses Lucene to index both text information and visual global descriptor of images. The descriptors for the image are created extracting the features resulting using AlexNet deep network (from levels 6 and 7) and transforming those features using a surrogate text representation (in order to exploit the capabilities of Lucene)
The end user can either submit a query consisting of:
- some text
- an image
- both text and an image.
The system finally provides the user with 40 ranked matches among the 25000 images of the dataset.
Source code available at: https://github.com/egidisa/MultiModalSearch
Media and Information Literacy (MIL) 4.MIL Media Literacy (Part 1)- Definitio...Arniel Ping
Learning Competencies
Learners will be able to…
1. define media literacy (SSHS);
2. discuss and value the importance of media literacy (SSHS);
3. explain the fundamental elements of media literacy (SSHS);
4. value the importance of critical thinking in media literacy (SSHS); and
5. apply critical thinking by identifying fallacies in arguments (SSHS).
Topic Outline
I- Media Literacy
A. Definition and Importance
B. Fundamental Elements of Media Literacy
C. Critical Thinking
1. Definition
2. Importance in Media Literacy
3. Fallacies of Thinking
Media and Information Literacy (MIL) - 6. Media and Information Languages (Pa...Arniel Ping
Topic
MIL - Media and Information Languages (Genre, Codes and Conventions)
Learning Competencies
1. evaluate everyday media and information with regard to codes, conventions, and messages; in regards to audience, producers, and other stakeholders (MIL11/12MILA-IIIf15)
2. produce and assess the codes, convention, and messages of a group presentation (MILI11/12MILA-IIIf16)
Media and Information Literacy (MIL) - 10. Media and Information Literate Ind...Arniel Ping
Content
10. Media and Information Literate Individual
a. Improved Quality of Life
b. Greater Political Participation
c.Better Economic Opportunities
d. Improved Learning Environment
e. More Cohesive Social Units
Learning Competency
1. Students will be able to synthesize the overall implication of media and information to an individual (personal, professional, educational, and others) and the society as a whole (economic, social, political, educational, and others) MIL11/12MILI-IIIj-29
Media and Information Literacy (MIL) - Intellectual Property, Fair Use, and C...Arniel Ping
Media and Information Literacy (MIL) Legal, Ethical, and Societal Issues in Media and Information (Part 1)
Topics:
1. Intellectual Property in International
and Local Context
2. Fair Use and Creative Commons
LEARNING COMPETENCIES:
1. explain intellectual property and its different types (SSHS);
2. explain copyright, fair use, etc.vis-a-vis human rights (MIL11/12LESI-IIIg20);
3. discuss current issues related to copyright vis-à-vis gov’t./provide sectors actions (MIL11/12LESI-IIIg21);
4. put into practice their understanding of the intellectual property, copy right, and fair use guidelines (MIL11/12LESI-IIIg17); and
5. explain actions to promote ethical use of media and information (MIL11/12LESI-IIIg22);
Lecture given on January 28, 2019 to post-graduate students of the Computer Engineering and Media program, at the School of Journalism and Media, Aristotle University of Thessaloniki.
Deep Learning: Changing the Playing Field of Artificial Intelligence - MaRS G...MaRS Discovery District
Deep learning is changing the field of artificial intelligence and revolutionizing our online experience, with applications including speech and image recognition. Information and communications technology giants such as Google, Facebook, IBM and Baidu, among others, are rapidly deploying deep learning into new products and services.
Behind all of the present-day excitement about deep learning are years of high risk and hard work by a small group of eminent computer scientists and theorists connected through the Canadian Institute for Advanced Research (CIFAR).
Wearable Computing and Human Computer InterfacesJeffrey Funk
These slides discuss how improvements in ICs, MEMS, cameras, and other electronic components are making wearable computing and new forms of human-computer interfaces economically feasible. Improvements in digital signal processing ICs and MEMS-based microphones are rapidly improving the technical and economical feasibility of voice-recognition based interfaces. Improvements in 2D and 3D image sensors (e.g., camera ICs) are rapidly improving the technical and economical feasibility of gesture-based interfaces, augmented reality, and virtual reality. Improvements in ICs, MEMS, displays and other components are rapidly making many forms of wearable computing economically feasible; these include many forms of head, arm, torso, and leg-mounted displays. Improvements in the materials for both non-invasive and invasive brain scans are rapidly improving the technical and economical feasibility of neural interfaces.
This talk explores the basics of AI and machine learning from an application point of view. We run through basic definitions and examples. Then we talk about management of AI/ML projects.
37 million reasons to give a damn about the disabledChris Merkel
Chris Merkel talks us through the hows and whys of accessibility design for websites.
During his presentation you'll learn what types of devices the disabled use to access the web, and see videos of real people using them. You'll learn practical tips for how to make our websites and apps more accessible and learn how to try out a screen reader for yourself.
Multimedia Information Retrieval: What is it, and why isn't ...
1. Video Search: Opportunities and Challenges Keynote Speech at ACM MIR Workshop ACM Multimedia Conference 2005 Singapore Dr. Ramesh R. Sarukkai Yahoo! Search { [email_address] [email_address] }
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21. Video Search: Features 1970 2000 1990 1980 2010 Texture: Autocorrelation; Wavelet transforms; Gabor Filters Shape: Edge Detectors; Moment invariants; Animate Vision Marr; Finite Element Methods; Shape from Motion; Color: Color Moments Color Histograms Color Autocorrelograms Segmentation: Scene segmentation; Scene Segmentation; Shot detection; OCR: Modeling; Successful OCR deployments; Face: Face Detection algorithms; Neural Networks; EigenFaces ASR: Acoustic analysis; HMMS; N-grams; CSR; LVCSR; Domain Specific; NIST Video TREC Starts Media IR systems Web Media Search
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