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The large amount of SIFT descriptors in an image and the high dimensionality of SIFT descriptor has made problems for large-scale image dataset in terms of speed and scalability. In this paper, we propose a descriptor selection algorithm via dictionary learning and only a small set of features are reserved, which we refer to as TOP-SIFT. We discover the inner relativity between the problem of descriptor...
Deformable shape retrieval has posed a challenge to researchers, which is becoming more and more important. This paper addresses non-rigid 3D shape retrieval in terms of a subtle adjustment strategy. For this purpose, we first construct a new global shape descriptor based on biharmonic distance, which uses the connectivity between vertices for natural shape representation. Then, in order to enhance...
With the emergence of the SHREC Contest, the retrieval performance of non-rigid 3D shapes has witnessed a great improvement. This paper mainly discusses how to improve the stability and discriminate ability for non-rigid 3D shape retrieval. We first introduce a robust global biharmonic (GBI) feature, which has achieved a balance between global and local shape properties. Then, a combination strategy...
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