Qualitative part-based models in content-based image retrieval
Machine Vision and Applications
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This paper addresses the problem of building generic 3D models of structured objects based on single 2D intensity images. In the context of this paper, generic modeling refers to the situation where analysis of the image information is performed on the sole basis of generic knowledge. That is, no a priori knowledge about the specific quantitative shape properties of the objects of interest is ever assumed. Moreover, images of interest are realistic. For instance, they may contain complex foreground 3D objects with textures and shadows, and a cluttered background. Their constituent parts and connections model objects. Therefore, a partly occluded object could be recognized from its model. Part models are based on geons, which are a set of qualitative generalized cylinders. An overview of the architecture of the modeling system is presented, along with the functionality of each subsystem and processing results.