Fazekas, Alexandru and Csetverikov, Dmitrij (2007) Analysis and performance evaluation of optical flow features for dynamic texture recognition. Signal Processing: Image Communication, 22 (7-8). pp. 680-691.

Full text not available from this repository.

Abstract

We address the problem of dynamic texture (DT) classification using optical flow features. optical flow based approaches dominate among the currently available DT classification methods. The features used by these approaches often describe local image distortions in terms of such quantities as curl or divergence. Both normal and complete flows have been considered, with normal flow being used more frequently. However, precise meaning and applicability of normal and complete flow features have never been analysed properly. We provide a principled analysis of local image distortions and their relation to optical flow. Then we present the results of a comprehensive DT classification study that compares the performances of different flow features for a normal flow algorithm and four different complete flow algorithms. The efficiencies of two flow confidence measures are also studied.

Item Type:	ISI Article
Uncontrolled Keywords:	dynamic texture, classification, optical flow
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Geometric Modelling and Computer Vision Laboratory
Depositing User:	Eszter Nagy
Date Deposited:	11 Dec 2012 15:30
Last Modified:	11 Dec 2012 15:30
URI:	https://eprints.sztaki.hu/id/eprint/5040

Update Item