期刊
PATTERN RECOGNITION LETTERS
卷 31, 期 12, 页码 1627-1632出版社
ELSEVIER
DOI: 10.1016/j.patrec.2010.05.009
关键词
Dynamic texture; Scientific image collections; Video segmentation; Video processing; Pattern recognition; Annotation
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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