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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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Journal ArticleDOI

Critical features for the recognition of biological motion.

TL;DR: It is concluded that recognition of biological motion might be accomplished by detecting mid-level optic flow features with relatively coarse spatial localization, and the computationally challenging reconstruction of precise position information from degraded stimuli might not be required.
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TL;DR: In this article, a method for human body pose estimation using depth map images from a depth camera is described. But the method is not suitable for the estimation of human body joints.
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Distance scalable no touch computing

TL;DR: In this paper, the authors present techniques for scaling and translating gestures such that the applicable gestures for control may vary depending on the user's distance from a gesture-based system. But they do not address the problem of defining and/or recognizing gestures.
References
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Proceedings ArticleDOI

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Proceedings ArticleDOI

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Journal ArticleDOI

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