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2007
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Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces

9 years 8 months ago
Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces
Object recognition and content-based image retrieval systems rely heavily on the accurate and efficient identification of shapes. A fundamental requirement in the shape analysis process is that shape similarities should be computed invariantly to basic geometric transformations, e.g. scaling, shifting, and most importantly, rotations. And while scale and shift invariance are easily achievable through a suitable shape representation, rotation invariance is much harder to deal with. In this work we explore the metric properties of the rotation invariant distance measures and propose an algorithm for fast similarity search in the shape space. The algorithm can be utilized in a number of important data mining tasks such as shape clustering and classification, or for discovering of motifs and discords in image collections. The technique is demonstrated to introduce a dramatic speed-up over the current approaches, and is guaranteed to introduce no false dismissals.
Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where SDM
Authors Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Wendy L. Hodges
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