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View-based object recognition using saliency maps
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DOI：10.1016/S0262-8856(98)00124-3.png)
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Abstract
En 中文
We introduce a novel view-based object representation, called the saliency map graph (SMG), which captures the salient regions of an object view at multiple scales using a wavelet transform. This compact representation is highly invariant to translation, rotation (image and depth), and scaling, and offers the locality of representation required for occluded object recognition. To compare two saliency map graphs, we introduce two graph similarity algorithms. The first computes the topological similarity between two SMGs, providing a coarse-level matching of two graphs. The second computes the geometrical similarity between two SMGs, providing a fine-level matching of two graphs. We test and compare these two algorithms on a large database of model object views. (C) 1999 Elsevier Science B.V. All rights reserved.
Keywords:
view-based object recognition
shape representation and recovery
graph matching
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