Rongjun Gao

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A novel 3D shape matching method is proposed in this paper. We first extract angular and distance feature pairs from pre-processed 3D models, then estimate their kernel densities after quantifying the feature pairs into a fixed number of bins. During 3D matching, we adopt the KL-divergence as a distance of 3D comparison. Experimental results show that our(More)
A fast and robust 3D retrieval method is proposed based on a novel weighted structural histogram representation. Our method has the following steps: 1) adaptively segment any 3D shape into a group of meaningful parts to generate local distribution matrixes, 2) integrate all the local distribution matrixes into a global distribution matrix, simultaneously(More)
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