Recognition of Humans and Their Activities Using Video

Recognition of Humans and Their Activities Using Video

Author: Rama Chellappa

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 171

ISBN-13: 303102236X

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The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. In this lecture, we discuss the use of face and gait signatures for human identification and recognition of human activities from video sequences. We survey existing work and describe some of the more well-known methods in these areas. We also describe our own research and outline future possibilities. In the area of face recognition, we start with the traditional methods for image-based analysis and then describe some of the more recent developments related to the use of video sequences, 3D models, and techniques for representing variations of illumination. We note that the main challenge facing researchers in this area is the development of recognition strategies that are robust to changes due to pose, illumination, disguise, and aging. Gait recognition is a more recent area of research in video understanding, although it has been studied for a long time in psychophysics and kinesiology. The goal for video scientists working in this area is to automatically extract the parameters for representation of human gait. We describe some of the techniques that have been developed for this purpose, most of which are appearance based. We also highlight the challenges involved in dealing with changes in viewpoint and propose methods based on image synthesis, visual hull, and 3D models. In the domain of human activity recognition, we present an extensive survey of various methods that have been developed in different disciplines like artificial intelligence, image processing, pattern recognition, and computer vision. We then outline our method for modeling complex activities using 2D and 3D deformable shape theory. The wide application of automatic human identification and activity recognition methods will require the fusion of different modalities like face and gait, dealing with the problems of pose and illumination variations, and accurate computation of 3D models. The last chapter of this lecture deals with these areas of future research.


Recognition of Humans and Their Activities Using Video

Recognition of Humans and Their Activities Using Video

Author: Rama Chellappa

Publisher: Morgan & Claypool Publishers

Published: 2006-01-01

Total Pages: 179

ISBN-13: 159829007X

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The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. In this lecture, we discuss the use of face and gait signatures for human identification and recognition of human activities from video sequences. We survey existing work and describe some of the more well-known methods in these areas. We also describe our own research and outline future possibilities. In the area of face recognition, we start with the traditional methods for image-based analysis and then describe some of the more recent developments related to the use of video sequences, 3D models, and techniques for representing variations of illumination. We note that the main challenge facing researchers in this area is the development of recognition strategies that are robust to changes due to pose, illumination, disguise, and aging. Gait recognition is a more recent area of research in video understanding, although it has been studied for a long time in psychophysics and kinesiology. The goal for video scientists working in this area is to automatically extract the parameters for representation of human gait. We describe some of the techniques that have been developed for this purpose, most of which are appearance based. We also highlight the challenges involved in dealing with changes in viewpoint and propose methods based on image synthesis, visual hull, and 3D models. In the domain of human activity recognition, we present an extensive survey of various methods that have been developed in different disciplines like artificial intelligence, image processing, pattern recognition, and computer vision. We then outline our method for modeling complex activities using 2D and 3D deformable shape theory. The wide application of automatic human identification and activity recognition methods will require the fusion of different modalities like face and gait, dealing with the problems of pose and illumination variations, and accurate computation of 3D models. The last chapter of this lecture deals with these areas of future research.


Human Activity Recognition

Human Activity Recognition

Author: Miguel A. Labrador

Publisher: CRC Press

Published: 2013-12-05

Total Pages: 206

ISBN-13: 1466588284

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Learn How to Design and Implement HAR Systems The pervasiveness and range of capabilities of today's mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sen


Human Activity Recognition and Prediction

Human Activity Recognition and Prediction

Author: Yun Fu

Publisher: Springer

Published: 2015-12-23

Total Pages: 179

ISBN-13: 3319270044

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This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.


Computer Vision -- ECCV 2014

Computer Vision -- ECCV 2014

Author: David Fleet

Publisher: Springer

Published: 2014-08-14

Total Pages: 855

ISBN-13: 331910599X

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The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.


Computer Vision - ECCV 2008

Computer Vision - ECCV 2008

Author: David Hutchison

Publisher:

Published: 2008

Total Pages: 0

ISBN-13: 9788354088684

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The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.


Semantic Analysis and Understanding of Human Behavior in Video Streaming

Semantic Analysis and Understanding of Human Behavior in Video Streaming

Author: Alberto Amato

Publisher: Springer Science & Business Media

Published: 2012-09-18

Total Pages: 111

ISBN-13: 1461454859

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Semantic Analysis and Understanding of Human Behaviour in Video Streaming investigates the semantic analysis of the human behaviour captured by video streaming, and introduces both theoretical and technological points of view. Video analysis based on the semantic content is in fact still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned. This book explores an innovative, original approach to human behaviour analysis and understanding by using the syntactical symbolic analysis of images and video streaming described by means of strings of symbols. A symbol is associated to each area of the analyzed scene. When a moving object enters an area, the corresponding symbol is appended to the string describing the motion. This approach allows for characterizing the motion of a moving object with a word composed by symbols. By studying and classifying these words we can categorize and understand the various behaviours. The main advantage of this approach lies in the simplicity of the scene and motion descriptions so that the behaviour analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. Besides, the structure of the representations is well suited for possible parallel processing, thus allowing for speeding up the analysis when appropriate hardware architectures are used. A new methodology for design systems for hierarchical high semantic level analysis of video streaming in narrow domains is also proposed. Guidelines to design your own system are provided in this book. Designed for practitioners, computer scientists and engineers working within the fields of human computer interaction, surveillance, image processing and computer vision, this book can also be used as secondary text book for advanced-level students in computer science and engineering.


Human Recognition in Unconstrained Environments

Human Recognition in Unconstrained Environments

Author: Maria De Marsico

Publisher: Academic Press

Published: 2017-01-09

Total Pages: 250

ISBN-13: 0081007124

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Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities