Human Body Part Segmentation of Interacting People by Learning Blob Models

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 m...

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Bibliographic Details
Published in2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing pp. 367 - 370
Main Authors Chi-Hung Chuang, Chun-Chieh Lee, Ying-Nong Chen, Jun-Wei Hsieh, Luo-Wei Tsai
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Biological system modeling
body part segmentation
Computational modeling
Gaussian mixture model
Humans
Image color analysis
Image segmentation
Legged locomotion
Video sequences
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Summary: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.
ISBN:1467317411
9781467317412
DOI:10.1109/IIH-MSP.2012.95