Abstract
This paper presents a novel framework for 3D object search and retrieval based on a query-by-range-image approach. Initially, salient features are extracted for both the query range image and the 3D target model that is followed by the estimation of the protrusion field generated by the extracted salient points of the 3D objects. Then, based on the concept that for a 3D object and a corresponding query range image, there should be a virtual camera with such intrinsic and extrinsic parameters that would generate an optimum range image, in terms of minimizing an error function that takes into account the protrusion field of the objects, when compared to other parameter sets or other target 3D models, matching is performed via estimating dissimilarity within the protrusion field. Experimental results illustrate the efficiency of the proposed approach even in the presence of noise or occlusion.
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Moustakas, K., Stavropoulos, G., Tzovaras, D. (2012). Protrusion Fields for 3D Model Search and Retrieval Based on Range Image Queries. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_58
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DOI: https://doi.org/10.1007/978-3-642-33179-4_58
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