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Proceedings ArticleDOI

Vision-Based Human Motion Recognition: A Survey

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TLDR
The research work in recent years have been analyzed and summarized, respectively from the classification of human motion, human motion feature extraction and recognition algorithm to introduce a number of humanmotion recognition.
Abstract
With the development of computer vision and image processing technology, human motion recognition, because of its wide range of applications, now has been attracting extensive attention in the field of computer vision. Vision-based recognition of people's motion not only includes the knowledge of image recognition and computer vision, but also involves the theory of recognition and artificial intelligence, so it is an extremely challenging interdisciplinary project. The research work in recent years have been analyzed and summarized, respectively from the classification of human motion, human motion feature extraction and recognition algorithm to introduce a number of human motion recognition.

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Citations
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Video-Based Abnormal Human Behavior Recognition—A Review

TL;DR: The main purpose of this survey is to extensively identify existing methods and characterize the literature in a manner that brings key challenges to attention.
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A survey of video datasets for human action and activity recognition

TL;DR: The survey introduced in this paper tries to cover the lack of a complete description of the most important public datasets for video-based human activity and action recognition and to guide researchers in the election of themost suitable dataset for benchmarking their algorithms.
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Occupancy Analysis of Sports Arenas Using Thermal Imaging

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Proximity Sensing Based on a Dynamic Vision Sensor for Mobile Devices

TL;DR: The proposed design of proximity sensing utilizing a dynamic vision sensor can eliminate environmental noises by using pattern matching based on time-domain analysis, whereas conventional optical proximity sensors, which are mainly used in smartphones, are very sensitive to environmental noises.
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Vision Tracking: A Survey of the State-of-the-Art

TL;DR: A comprehensive review of the state-of-the art visual tracking methods is reported on different performance metrics to evaluate the efficiency of visual tracking algorithms which might help researchers to identify new avenues in this area.
References
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Journal ArticleDOI

The recognition of human movement using temporal templates

TL;DR: A view-based approach to the representation and recognition of human movement is presented, and a recognition method matching temporal templates against stored instances of views of known actions is developed.
Journal ArticleDOI

A Survey of Computer Vision-Based Human Motion Capture

TL;DR: A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented, with a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition.
Proceedings ArticleDOI

Human motion analysis: a review

TL;DR: The paper gives an overview of the various tasks involved in motion analysis of the human body, and focuses on three major areas related to interpreting human motion: motion analysis involving human body parts, tracking of human motion using single or multiple cameras, and recognizing human activities from image sequences.
Journal ArticleDOI

Human Motion Analysis

TL;DR: An overview of the various tasks involved in motion analysis of the human body is given and three major areas related to interpreting human motion are focused on: motion analysis involving human body parts, tracking a moving human from a single view or multiple camera perspectives, and recognizing human activities from image sequences.
Proceedings ArticleDOI

Recognizing human action in time-sequential images using hidden Markov model

TL;DR: The recognition rate is improved by increasing the number of people used to generate the training data, indicating the possibility of establishing a person-independent action recognizer.
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