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Workshop/Tutorial/Competition: Computational Symmetry in Computer Vision

Workshop/Tutorial/Competition: Computational Symmetry in Computer Vision
研讨会/教程/竞赛:计算机视觉中的计算对称性
批准号:
1040711
负责人:
Yanxi Liu
金额:
$2.85万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-06-15 至 2012-05-31

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中文摘要
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英文摘要
Humans, animals and insects have an innate ability to perceive and take advantage of symmetry, which is a pervasive phenomenon presenting itself in all forms and scales in natural and man-made environments. Although our understanding of repeated patterns is generalized by the mathematical concept of symmetries and group theory, perception and recognition of symmetry has yet to be fully explored in machine intelligence and computer vision, and few effective computational methods are available today. In response to a resurging interest in computational symmetry with the vision community, this timely and unique workshop/tutorial/competition is organized to investigate this potentially powerful intermediate level tool.The event has three main parts:(1) a multidisciplinary perspective on the importance and lasting impact of symmetry, presented by a worldwide group of distinguished speakers;(2) a detailed summary of the mathematical theory, state of the art algorithms and a diverse set of applications (successes and failures); and(3) the algorithms and the outcome of the symmetry detection competition, presented by the top three performers on the benchmarked symmetry detection algorithm competition.Active participations by computer vision researchers, especially graduate students, in this event are expected, leading to broadened understanding and appreciation of symmetry in all participants, as well as an acute and lasting impact to their research and their use of computational symmetry tools. A website with the content of the workshop/tutorial, the competition process and final results is set up before and augmented after the workshop, for public access.
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会议论文
RI: Small: Explicit and Implicit Regularity Perception
INSPIRE: Symmetry Group-based Regularity Perception in Human and Computer Vision
USA-Sino Summer School in Vision, Learning, Pattern Recognition, VLPR 2012
EAGER: Recurring Pattern Discovery
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