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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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Patent

Image segmentation using reduced foreground training data

TL;DR: In this paper, the foreground and background training data for image segmentation are determined by optimization of a modified energy function, which is the energy function used in image segmentations with an additional term comprising a scalar value.
Patent

Interactive content creation

TL;DR: In this article, a depth camera or other sensor is used to detect that a user (or a portion of the user) entered a first collision volume of a plurality of collision volumes.

Human Action Classification Using SVM 2K Classif ier on Motion Features

TL;DR: The new SVM_2K classifier is introduced that can achieve improved performance over a standard SVM by combining two types of motion feature vector together and be efficient and may be used in real-time human action classification systems.
Book ChapterDOI

Modeling and Recognition of Complex Human Activities

TL;DR: The ability to recognize complex behaviors involving multiple interacting objects is a very challenging problem and future work needs to study its various aspects of features, recognition strategies, models, robustness issues, and context.
Journal Article

A view-based multiple objects tracking and human action recognition for interactive virtual environments

TL;DR: This research is supported by Foundation of ubiquitous computing and networking project (UCN) Project, the Ministry of Knowledge Economy (MKE) 21st Century Frontier R&D Program in Korea and a result of subproject UCN 08B3-O4-10M.
References
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Proceedings ArticleDOI

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Journal ArticleDOI

Pfinder: real-time tracking of the human body

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TL;DR: The human visual process can be studied by examining the computational problems associated with deriving useful information from retinal images by applying the approach to the problem of representing three-dimensional shapes for the purpose of recognition.
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.
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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