Journal
PATTERN RECOGNITION LETTERS
Volume 31, Issue 12, Pages 1627-1632Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2010.05.009
Keywords
Dynamic texture; Scientific image collections; Video segmentation; Video processing; Pattern recognition; Annotation
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We present the DynTex database of high-quality dynamic texture videos. It consists of over 650 sequences of dynamic textures, mostly in everyday surroundings. Additionally, we propose a scheme for the manual annotation of the sequences based on a detailed analysis of the physical processes underlying the dynamic textures. Using this scheme we describe the texture sequences in terms of both visual structure and semantic content. The videos and annotations are made publicly available for scientific research. (C) 2010 Elsevier B.V. All rights reserved.
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