Dynamic texture recognition using optical flow features and temporal periodicity

被引：15
|
作者：
Fazekas, Sandor [1 ]
Chetverikov, Dmitry [1 ]
机构：
[1] Comp & Automat Res Inst, Kende 13-17, H-1111 Budapest, Hungary
来源：
2007 INTERNATIONAL WORKSHOP ON CONTENT-BASED MULTIMEDIA INDEXING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/CBMI.2007.385388
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
We address the problem of dynamic texture (DT) classification using optical flow features. Optical flow based approaches dominate among the currently available DT recognition methods. We introduce rotation- and scale-invariant DT features based on local image distortions computed via optical flow. Then we describe an SVD-based method for measuring the degree of temporal periodicity of a dynamic texture. Finally, we present the results of a DT classification study that compares the performances of different flow features for normal and complete optical flows.
引用
收藏
页码：25 / +
页数：3
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