Please use this identifier to cite or link to this item: https://doi.org/10.1145/956750.956818
Title: Mining viewpoint patterns in image databases
Authors: Hsu, W. 
Dai, J.
Lee, M.L. 
Keywords: Image database
Image mining
Spatial relationship
Issue Date: 2003
Source: Hsu, W.,Dai, J.,Lee, M.L. (2003). Mining viewpoint patterns in image databases. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining : 553-558. ScholarBank@NUS Repository. https://doi.org/10.1145/956750.956818
Abstract: The increasing number of image repositories has made image mining an important task because of its potential in discovering useful image patterns from a large set of images. In this paper, we introduce the notion of viewpoint patterns for image databases. Viewpoint patterns refer to patterns that capture the invariant relationships of one object from the point of view of another object. These patterns are unique and significant in images because the absolute positional information of objects for most images is not important, but rather, it is the relative distance and orientation of the objects from each other that is meaningful. We design a scalable and efficient algorithm to discover such viewpoint patterns. Experiments results on various image sets demonstrate that viewpoint patterns are meaningful and interesting to human users. Copyright 2003 ACM.
Source Title: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
URI: http://scholarbank.nus.edu.sg/handle/10635/40104
DOI: 10.1145/956750.956818
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