Abstract
Recent advances in modeling, digitization, and visualization of three-dimensional shapes have led to a surge in the number of available three-dimensional models. Therefore, the technology of three-dimensional retrieval becomes very necessary. This paper introduces a content-based 3D models retrieval method. We propose a unified framework to deal with the complex mesh structure of three-dimensional models, which has one-dimensional potentials describing local similarity and higher-order potentials describing spatial consistency. A three-dimensional surface extension is proposed, which describes the three-dimensional graph as a set of local rotation and scale invariant points. Effective indexing and approximate optimization techniques are also used to speed up MRF reasoning.
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Li, Q., Xue, J. (2020). Shape Retrieval for 3D Models Based on MRF. In: Kountchev, R., Patnaik, S., Shi, J., Favorskaya, M. (eds) Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology. Smart Innovation, Systems and Technologies, vol 179. Springer, Singapore. https://doi.org/10.1007/978-981-15-3863-6_2
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DOI: https://doi.org/10.1007/978-981-15-3863-6_2
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