Learning A Stable Structure To Describe Dynamic Texture

Abstract

We are interested in descriptors for dynamic textures that supports both further analysis and resynthesis applications. These tasks demand that the description encodes appearance and motion separably. This paper shows that a tree hierarchy which is built from nested image regions can be acquired via analysis of the first few frames of a video sequence. The tree is stable over space and time and leads to a measurably improved performance on the generic application of tracking the dynamic texture itself. The claim is supported by experimental data taken from a range of dynamic textures including trees and flowers. We conclude that both appearance and motion are better described using the stable structure rather than by a sequence of equivalent hierarchies each optimised for a single frame, because motion data helps to reduce clutter artefacts from trees built for static images.

DOI: 10.5244/C.22.3

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@inproceedings{Li2008LearningAS, title={Learning A Stable Structure To Describe Dynamic Texture}, author={Chuan Li and Peter M. Hall}, booktitle={BMVC}, year={2008} }