Comparison of 3D local and global descriptors for similarity retrieval of range data

Author:

Bayramoglu Neslihan,Alatan A. Aydın

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference55 articles.

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3. J. Machado, A. Ferreira, P.B. Pascoal, M. Abdelrahman, M. Aono, M. El-Melegy, A. Farag, H. Johan, B. Li, Y. Lu, et al., Shrec’13 track: retrieval of objects captured with low-cost depth-sensing cameras, in: Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval, 2013, pp. 65–71.

4. K. Lai, L. Bo, X. Ren, D. Fox, A large-scale hierarchical multi-view rgb-d object dataset, in: 2011 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Shanghai, China, 2011, pp. 1817–1824.

5. Kinect, Kinect - xbox.com 〈http://www.xbox.com/en-US/Kinect/〉, January 2013.

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1. Nonrigid 3D Shape Retrieval with HAPPS: A Novel Hybrid Augmented Point Pair Signature;2019 International Conference on Computational Science and Computational Intelligence (CSCI);2019-12

2. Effectiveness of the bag-of-words approach on the object search problem in 3D domain;Proceedings of the 33rd Spring Conference on Computer Graphics;2017-05-15

3. Multi-scale object retrieval via learning on graph from multimodal data;Neurocomputing;2016-09

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