期刊
COMPUTER GRAPHICS FORUM
卷 30, 期 7, 页码 2011-2020出版社
WILEY
DOI: 10.1111/j.1467-8659.2011.02050.x
关键词
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We propose a sketch-based 3D shape retrieval system that is substantially more discriminative and robust than existing systems, especially for complex models. The power of our system comes from a combination of a contour-based 2D shape representation and a robust sampling-based shape matching scheme. They are defined over discriminative local features and applicable for partial sketches; robust to noise and distortions in hand drawings; and consistent when strokes are added progressively. Our robust shape matching, however, requires dense sampling and registration and incurs a high computational cost. We thus devise critical acceleration methods to achieve interactive performance: precomputing kNN graphs that record transformations between neighboring contour images and enable fast online shape alignment; pruning sampling and shape registration strategically and hierarchically; and parallelizing shape matching on multi-core platforms or GPUs. We demonstrate the effectiveness of our system through various experiments, comparisons, and user studies.
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