A comparison on textured motion classification

Authors:
Kaan Öztekin;Gözde Bozdağı Akar
Affiliations:
Department of Electrical and Electronics Engineering, Middle East Technical University;Department of Electrical and Electronics Engineering, Middle East Technical University
Venue:
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Year:
2006

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Abstract

Textured motion – generally known as dynamic or temporal texture – analysis, classification, synthesis, segmentation and recognition is popular research areas in several fields such as computer vision, robotics, animation, multimedia databases etc. In the literature, several algorithms are proposed to characterize these textured motions such as stochastic and deterministic algorithms. However, there is no study which compares the performances of these algorithms. In this paper, we carry out a complete comparison study. Also, improvements to deterministic methods are given.