Evaluation of Point Cloud Categorization for Rigid and Non-Rigid 3D Objects-Reference-Cited by-同舟云学术

Evaluation of Point Cloud Categorization for Rigid and Non-Rigid 3D Objects

Published:2018-12-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing
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Author:

Setty Shankar¹,Hegde Sindhu B.¹,Satyappanavar Supriya¹,Mudenagudi Uma¹

Affiliation:

1. K. L. E. Technological University, Hubballi, Karnataka, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3293353.3293413

Reference47 articles.

1. M. Aubry U. Schlickewei and D. Cremers. 2011. The wave kernel signature: A quantum mechanical approach to shape analysis. In ICCV. 1626--1633. M. Aubry U. Schlickewei and D. Cremers. 2011. The wave kernel signature: A quantum mechanical approach to shape analysis. In ICCV. 1626--1633.

2. Mikhail Belkin Jian Sun and Yusu Wang. 2009. Constructing Laplace Operator from Point Clouds in Rd (SODA). 1031--1040. Mikhail Belkin Jian Sun and Yusu Wang. 2009. Constructing Laplace Operator from Point Clouds in Rd (SODA). 1031--1040.

3. Yizhak Ben-Shabat Michael Lindenbaum and Anath Fischer. 2017. 3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks. CoRR (2017). Yizhak Ben-Shabat Michael Lindenbaum and Anath Fischer. 2017. 3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks. CoRR (2017).

5. M. M. Bronstein and I. Kokkinos. 2010. Scale-invariant heat kernel signatures for non-rigid shape recognition. In CVPR. 1704--1711. M. M. Bronstein and I. Kokkinos. 2010. Scale-invariant heat kernel signatures for non-rigid shape recognition. In CVPR. 1704--1711.