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This paper proposes a new framework for an efficient detection of template shapes within a target 3D model, or scene. The proposed approach distinguishes from the previous literature because the part-in-whole matching between the template and the target is obtained by extracting off-line only the shape descriptor of the template, while the description of the target is dynamically and adaptively extracted during the matching process. This novel framework, called the Fast Reject schema, exploits the incremental nature of a class of local shape descriptors to significantly reduce the part-in-whole matching time, without any expensive processing of the models for the extraction of the shape descriptors. The schema have been tested on three different descriptors and results are discussed in details. Experiments show that the gain in computational performances does not compromise the accuracy of the matching results.

The fast reject schema for part-in-whole 3D shape matching