Abstract
In this paper, we introduce a novel shape-based interest point (SIP) descriptor to encode local surface shapes for three-dimensional (3D) ear recognition; the descriptor provides an advantage over previous descriptors by capturing greater details of the macro-shape patterns surrounding an interest point. Using the SIP descriptor, a function is developed to measure the shape dissimilarity between any two interest points. Finally, in the recognition stage, a probe and a gallery pair are compared by applying the matching algorithm on the interest points, with the similarity score set as the number of matched interest points. The proposed method has been tested on the University of Notre Dame(UND) collection J2 dataset, containing range images of 415 subjects. The experimental results demonstrate that our method achieves a 97.4% rank-one recognition rate and a 2.0% Equal Error Rate (EER), which outperforms the state-of-the-art methods.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings |
| Pages | 4176-4180 |
| Number of pages | 5 |
| DOIs | |
| State | Published - Dec 1 2013 |
| Event | 2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia Duration: Sep 15 2013 → Sep 18 2013 |
Other
| Other | 2013 20th IEEE International Conference on Image Processing, ICIP 2013 |
|---|---|
| Country | Australia |
| City | Melbourne, VIC |
| Period | 9/15/13 → 9/18/13 |
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Keywords
- 3D ear recognition
- local feature
- shape matching
- shape-based interest point descriptor
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
Cite this
A novel shape-based interest point descriptor (SIP) for 3D ear recognition. / Lei, Jiajia; Zhou, Jindan; Abdel-Mottaleb, Mohamed.
2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. 2013. p. 4176-4180 6738860.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A novel shape-based interest point descriptor (SIP) for 3D ear recognition
AU - Lei, Jiajia
AU - Zhou, Jindan
AU - Abdel-Mottaleb, Mohamed
PY - 2013/12/1
Y1 - 2013/12/1
N2 - In this paper, we introduce a novel shape-based interest point (SIP) descriptor to encode local surface shapes for three-dimensional (3D) ear recognition; the descriptor provides an advantage over previous descriptors by capturing greater details of the macro-shape patterns surrounding an interest point. Using the SIP descriptor, a function is developed to measure the shape dissimilarity between any two interest points. Finally, in the recognition stage, a probe and a gallery pair are compared by applying the matching algorithm on the interest points, with the similarity score set as the number of matched interest points. The proposed method has been tested on the University of Notre Dame(UND) collection J2 dataset, containing range images of 415 subjects. The experimental results demonstrate that our method achieves a 97.4% rank-one recognition rate and a 2.0% Equal Error Rate (EER), which outperforms the state-of-the-art methods.
AB - In this paper, we introduce a novel shape-based interest point (SIP) descriptor to encode local surface shapes for three-dimensional (3D) ear recognition; the descriptor provides an advantage over previous descriptors by capturing greater details of the macro-shape patterns surrounding an interest point. Using the SIP descriptor, a function is developed to measure the shape dissimilarity between any two interest points. Finally, in the recognition stage, a probe and a gallery pair are compared by applying the matching algorithm on the interest points, with the similarity score set as the number of matched interest points. The proposed method has been tested on the University of Notre Dame(UND) collection J2 dataset, containing range images of 415 subjects. The experimental results demonstrate that our method achieves a 97.4% rank-one recognition rate and a 2.0% Equal Error Rate (EER), which outperforms the state-of-the-art methods.
KW - 3D ear recognition
KW - local feature
KW - shape matching
KW - shape-based interest point descriptor
UR - http://www.scopus.com/inward/record.url?scp=84897792367&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897792367&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2013.6738860
DO - 10.1109/ICIP.2013.6738860
M3 - Conference contribution
SN - 9781479923410
SP - 4176
EP - 4180
BT - 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
ER -