3D face recognition based on fast feature detection and non-rigid iterative closest point

Can Tong; Sei Ichiro Kamata; Alireza Ahrary

doi:10.1109/ICICISYS.2009.5357633

3D face recognition based on fast feature detection and non-rigid iterative closest point

Can Tong^*, Sei Ichiro Kamata, Alireza Ahrary

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents a 3D face recognition algorithm using fast landmark detection and non-rigid iterative Closest Point (ICP) algorithm. The proposed approach can estimate the facial feature region using the anthropometric face model after pose correction, and accurately detect 9 facial landmarks (nose tip, sellion, inner and outer eye corners, nostrils and mouth center). An extension of ICP algorithm has also been proposed to matching the non-rigid 3D face shapes. Experimental results demonstrate that compared to the existing methods, the proposed approach can efficiently detect human facial landmarks and satisfactorily deal with the 3D face matching problem.

Original language	English
Title of host publication	Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Pages	509-512
Number of pages	4
DOIs	https://doi.org/10.1109/ICICISYS.2009.5357633
Publication status	Published - 2009
Event	2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 - Shanghai, China Duration: 2009 Nov 20 → 2009 Nov 22

Publication series

Name	Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Volume	4

Conference

Conference	2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Country/Territory	China
City	Shanghai
Period	09/11/20 → 09/11/22

Keywords

3D face recognition
Anthropometric face model
ICP
Landmark detection
Non-rigid

ASJC Scopus subject areas

Computer Science(all)
Control and Systems Engineering

Access to Document

10.1109/ICICISYS.2009.5357633

Cite this

Tong, C., Kamata, S. I., & Ahrary, A. (2009). 3D face recognition based on fast feature detection and non-rigid iterative closest point. In Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 (pp. 509-512). [5357633] (Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009; Vol. 4). https://doi.org/10.1109/ICICISYS.2009.5357633

3D face recognition based on fast feature detection and non-rigid iterative closest point. / Tong, Can; Kamata, Sei Ichiro; Ahrary, Alireza.
Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009. 2009. p. 509-512 5357633 (Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tong, C, Kamata, SI & Ahrary, A 2009, 3D face recognition based on fast feature detection and non-rigid iterative closest point. in Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009., 5357633, Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009, vol. 4, pp. 509-512, 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009, Shanghai, China, 09/11/20. https://doi.org/10.1109/ICICISYS.2009.5357633

Tong C, Kamata SI, Ahrary A. 3D face recognition based on fast feature detection and non-rigid iterative closest point. In Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009. 2009. p. 509-512. 5357633. (Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009). doi: 10.1109/ICICISYS.2009.5357633

Tong, Can ; Kamata, Sei Ichiro ; Ahrary, Alireza. / 3D face recognition based on fast feature detection and non-rigid iterative closest point. Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009. 2009. pp. 509-512 (Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009).

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title = "3D face recognition based on fast feature detection and non-rigid iterative closest point",

abstract = "This paper presents a 3D face recognition algorithm using fast landmark detection and non-rigid iterative Closest Point (ICP) algorithm. The proposed approach can estimate the facial feature region using the anthropometric face model after pose correction, and accurately detect 9 facial landmarks (nose tip, sellion, inner and outer eye corners, nostrils and mouth center). An extension of ICP algorithm has also been proposed to matching the non-rigid 3D face shapes. Experimental results demonstrate that compared to the existing methods, the proposed approach can efficiently detect human facial landmarks and satisfactorily deal with the 3D face matching problem.",

keywords = "3D face recognition, Anthropometric face model, ICP, Landmark detection, Non-rigid",

author = "Can Tong and Kamata, {Sei Ichiro} and Alireza Ahrary",

year = "2009",

doi = "10.1109/ICICISYS.2009.5357633",

language = "English",

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note = "2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 ; Conference date: 20-11-2009 Through 22-11-2009",

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N2 - This paper presents a 3D face recognition algorithm using fast landmark detection and non-rigid iterative Closest Point (ICP) algorithm. The proposed approach can estimate the facial feature region using the anthropometric face model after pose correction, and accurately detect 9 facial landmarks (nose tip, sellion, inner and outer eye corners, nostrils and mouth center). An extension of ICP algorithm has also been proposed to matching the non-rigid 3D face shapes. Experimental results demonstrate that compared to the existing methods, the proposed approach can efficiently detect human facial landmarks and satisfactorily deal with the 3D face matching problem.

AB - This paper presents a 3D face recognition algorithm using fast landmark detection and non-rigid iterative Closest Point (ICP) algorithm. The proposed approach can estimate the facial feature region using the anthropometric face model after pose correction, and accurately detect 9 facial landmarks (nose tip, sellion, inner and outer eye corners, nostrils and mouth center). An extension of ICP algorithm has also been proposed to matching the non-rigid 3D face shapes. Experimental results demonstrate that compared to the existing methods, the proposed approach can efficiently detect human facial landmarks and satisfactorily deal with the 3D face matching problem.

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KW - Anthropometric face model

KW - ICP

KW - Landmark detection

KW - Non-rigid

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3D face recognition based on fast feature detection and non-rigid iterative closest point

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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