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Projective analysis is an important solution for 3D shape retrieval, sincehuman visual perceptions of 3D shapes rely on various 2D observations fromdifferent view points. Although multiple informative and discriminative viewsare utilized, most projection-based retrieval systems suffer from heavycomputational cost, thus cannot satisfy the basic requirement of scalabilityfor search engines. In this paper, we present a real-time 3D shape searchengine based on the projective images of 3D shapes. The real-time property ofour search engine results from the following aspects: (1) efficient projectionand view feature extraction using GPU acceleration; (2) the first invertedfile, referred as F-IF, is utilized to speed up the procedure of multi-viewmatching; (3) the second inverted file (S-IF), which captures a localdistribution of 3D shapes in the feature manifold, is adopted for efficientcontext-based re-ranking. As a result, for each query the retrieval task can befinished within one second despite the necessary cost of IO overhead. We namethe proposed 3D shape search engine, which combines GPU acceleration andInverted File Twice, as GIFT. Besides its high efficiency, GIFT alsooutperforms the state-of-the-art methods significantly in retrieval accuracy onvarious shape benchmarks and competitions.

GIFT: A Real-time and Scalable 3D Shape Search Engine