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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44051

Title: Human Body Part Segmentation of Interacting People by Learning Blob Models
Authors: Chi-Hung Chuang
Jun-Wei Hsieh
Chun-Chieh Lee
Ying-Nong Chen
Luo-Wei Tsai
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: body part segmentation
Gaussian mixture model
Date: 2012-07
Issue Date: 2017-11-13T07:27:46Z
Publisher: The Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Abstract: Abstract:In this paper, a scheme is proposed for solving segmentation problem when people engage in body contact in a video sequence. First, the body parts belonging to each interacting person are extracted using the deformable triangulation technique. The color blobs of each person are learned by Gaussian mixtures model on the fly before the person is interacting with another. Finally, those learned blob models are employed as decision criteria to segment each involved person out. The experimental results show that the proposed approach handles this kind of segmentation in an effective way.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44051
Appears in Collections:[資訊工程學系] 演講及研討會

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