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Proceedings ArticleDOI

Human motion analysis: a review

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TLDR
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.
Abstract
Human motion analysis is receiving increasing attention from computer vision researchers. This interest is motivated by a wide spectrum of applications, such as athletic performance analysis, surveillance, man-machine interfaces, content-based image storage and retrieval, and video conferencing. The paper gives an overview of the various tasks involved in motion analysis of the human body. The authors focus on three major areas related to interpreting human motion: 1) motion analysis involving human body parts, 2) tracking of human motion using single or multiple cameras, and 3) recognizing human activities from image sequences. Motion analysis of human body parts involves the low-level segmentation of the human body into segments connected by joints, and recovers the 3D structure of the human body using its 2D projections over a sequence of images. Tracking human motion using a single or multiple camera focuses on higher-level processing, in which moving humans are tracked without identifying specific parts of the body structure. After successfully matching the moving human image from one frame to another in image sequences, understanding the human movements or activities comes naturally, which leads to a discussion of recognizing human activities. The review is illustrated by examples.

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Citations
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Proceedings ArticleDOI

Incremental clustering of gesture patterns based on a self organizing incremental neural network

TL;DR: A Hidden Markov Model (HMM) based SOINN (HB-SOINN) is proposed, which outperforms other methods with respect to incremental clustering gesture data, and contributes to robust feature extraction from sequence patterns.
Proceedings ArticleDOI

Scale-based human motion representation for action recognition

TL;DR: The possibility of developing more general action recognition algorithms by systematic reduction of complexity of human motion, instead of designing more and more complex algorithms is explored and a particular problem of detecting the action of athlete hitting the ball with a racquet in the game of squash is tested.
Journal ArticleDOI

Active Contours Level Set Based Still Human Body Segmentation from Depth Images For Video-based Activity Recognition

TL;DR: An active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR and not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise.
Proceedings ArticleDOI

Integrated audiovisual processing for object localization and tracking

TL;DR: It is shown that combining a speech source localization algorithm with a video-based head tracking algorithm results in a more accurate and robust tracker than that obtained using any one of the audio or visual modalities.
Journal ArticleDOI

Analysis of composite gestures with a coherent probabilistic graphical model

TL;DR: A probabilistic framework that incorporates both static and dynamic gesture primitives, called Gesture Words, and a greedy algorithm for performing inference on the PGM to facilitate online computation.
References
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Proceedings ArticleDOI

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Journal ArticleDOI

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TL;DR: The author uses projective relations as the theoretical foundation of his investigations of visual space and motion and concludes that during locomotion the components of the human visual environment are interpreted as rigid structures in relative motion.
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