Chaotic features for motion pattern segmentation and dynamic texture classifiation

被引：0
作者：
机构：
[1] School of Aeronautics and Astronautics, Shanghai Jiao Tong University
来源：
Hu, S.-Q. (sqhu@sjtu.edu.cn) | 1600年 / Science Press卷 / 40期
关键词：
Chaotic features; Dynamic texture; Earth mover's distance (EMD); Mean shift;
D O I：
10.3724/SP.J.1004.2014.00604
中图分类号：
学科分类号：
摘要：
In this paper, we propose a novel framework for dynamical texture modeling based on chaos theory. Our method first extracts features from dynamical texutre and concatenate the features to a feature vector. A video is then represented by a feature matrix. The mean shift clustering algorithm is used to cluster the feature vector which achieves segmenting videos into diffrent motion patterns. The earth mover's distance (EMD) is employed to compute the feature cluster similarities and classify the dynamic textures. Experimental results indicate that: 1) The segmentation algorithm can cluster diffrent motion patterns in videos; 2) The feature vector proposed in this paper can effctively characterize the dynamical texture; 3) The proposed algorithm can classify dynamical texture accurately. In addition, the algorithm is robust to video noise. © 2014 Acta Automatica Sinica. All rights reserved.
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页码：604 / 614
页数：10
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