Abstract
In this paper, we propose a new framework for segmentation and deformation estimation in texture-less point clouds. Given a reference point cloud and a corresponding deformed point cloud, our approach first segments both the point clouds using OBB-LBS (Oriented Bounding Box-Laplace Beltrami Spectral) and estimates the semi-global dense spectral shape descriptors. These coarse descriptors identify the segments which need to be further investigated for localizing the area of deformation at a finer level.
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Kalyani, J., Vaiapury, K., Parameswaran, L. (2019). A Spectral Approach for Segmentation and Deformation Estimation in Point Cloud Using Shape Descriptors. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_41
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DOI: https://doi.org/10.1007/978-3-030-00665-5_41
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