Performance evaluation of 3D local surface descriptors for low and high resolution range image registration

S.A.A. Shah; Mohammed Bennamoun; Farid Boussaïd

doi:10.1109/DICTA.2014.7008123

Performance evaluation of 3D local surface descriptors for low and high resolution range image registration

S.A.A. Shah, Mohammed Bennamoun, Farid Boussaïd

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

12 Citations (Scopus)

Abstract

© 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.

Original language	English
Title of host publication	2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-7
Volume	N/A
ISBN (Print)	9781479954094
DOIs	https://doi.org/10.1109/DICTA.2014.7008123
Publication status	Published - 2014
Event	2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA) - Wollongong, Australia Duration: 25 Nov 2014 → 27 Nov 2014

Conference

Conference	2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA)
Abbreviated title	DICTA 2014
Country/Territory	Australia
City	Wollongong
Period	25/11/14 → 27/11/14

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10.1109/DICTA.2014.7008123

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Shah, S. A. A., Bennamoun, M., & Boussaïd, F. (2014). Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. In 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (Vol. N/A, pp. 1-7). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DICTA.2014.7008123

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author = "S.A.A. Shah and Mohammed Bennamoun and Farid Boussa{\"i}d",

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Shah, SAA , Bennamoun, M & Boussaïd, F 2014, Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. in 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). vol. N/A, IEEE, Institute of Electrical and Electronics Engineers, pp. 1-7, 2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA), Wollongong, New South Wales, Australia, 25/11/14. https://doi.org/10.1109/DICTA.2014.7008123

Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. / Shah, S.A.A.; Bennamoun, Mohammed ; Boussaïd, Farid.
2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). Vol. N/A IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 1-7.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

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N2 - © 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.

AB - © 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.

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DO - 10.1109/DICTA.2014.7008123

M3 - Conference paper

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BT - 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA)

Y2 - 25 November 2014 through 27 November 2014

ER -

Performance evaluation of 3D local surface descriptors for low and high resolution range image registration

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