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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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Object tracking: A survey

TL;DR: The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends to discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
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Kernel-based object tracking

TL;DR: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed, which employs a metric derived from the Bhattacharyya coefficient as similarity measure, and uses the mean shift procedure to perform the optimization.
Proceedings ArticleDOI

Recognizing human actions: a local SVM approach

TL;DR: This paper construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition and presents the presented results of action recognition.
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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.
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A survey of socially interactive robots

TL;DR: The context for socially interactive robots is discussed, emphasizing the relationship to other research fields and the different forms of “social robots”, and a taxonomy of design methods and system components used to build socially interactive Robots is presented.
References
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Journal ArticleDOI

State space reconstruction in the presence of noise

TL;DR: In this article, the authors extend Takens' treatment, applying statistical methods to incorporate the effects of observational noise and estimation error, and derive asymptotic scaling laws for distortion and noise amplification.
Proceedings ArticleDOI

Model-based tracking of self-occluding articulated objects

TL;DR: This work describes a framework for local trading of self occluding motion, in which one part of an object obstructs the visibility of another, using a kinematic model to predict occlusions and windowed templates to track partially occluded objects.
Journal ArticleDOI

Towards model-based recognition of human movements in image sequences

TL;DR: A model-based approach for the recognition of pedestrians is introduced and the human body is represented by a 3D-model consisting of cylinders, whereas for modelling the movement of walking the authors use data from medical motion studies.

Image Analysis of Human Motion Using Constraint Propagation

TL;DR: In this paper, a system capable of analyzing image sequences of human motion is described, which is structured as a feedback loop between high and low levels: predictions are made at the semantic level, and verifications are sought at the image level.
Journal ArticleDOI

Model-based image analysis of human motion using constraint propagation

TL;DR: A system capable of analyzing image sequences of human motion is described, structured as a feedback loop between high and low levels: predictions are made at the semantic level and verifications are sought at the image level.
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