Discriminative Sketch-based 3D Model Retrieval via Robust Shape Matching
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Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
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 contourbased 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.
Description
@article{10.1111:j.1467-8659.2011.02050.x,
journal = {Computer Graphics Forum},
title = {{Discriminative Sketch-based 3D Model Retrieval via Robust Shape Matching}},
author = {Shao, Tianjia and Xu, Weiwei and Yin, Kangkang and Wang, Jingdong and Zhou, Kun and Guo, Baining},
year = {2011},
publisher = {The Eurographics Association and Blackwell Publishing Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/j.1467-8659.2011.02050.x}
}