Histograms of categorized shapes for 3D ear detection

Jindan Zhou, Steven Cadavid, Mohamed Abdel-Mottaleb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)

Abstract

We introduce a novel shape-based feature set, termed the Histograms of Categorized Shapes (HCS), for robust Three-Dimensional (3D) object recognition. By adopting the sliding window approach and a linear Support Vector Machine (SVM) classifier, the efficacy of the HCS feature is assessed on a 3D ear detection task. Experimental results demonstrate that the approach achieves a perfect detection rate, i.e., a 100% detection rate with a 0% false positive rate, on a validation set consisting of 142 range profile images from the University of Notre Dame (UND) 3D ear biometrics database. It is to the best of our knowledge that the detection rate achieved here outperforms those reported in the literature for the given dataset. The proposed detector is also extremely efficient in both training and detection due to the simplicity of the feature extraction and speed of the classification process, suggesting that the method is suitable for practical use in 3D ear biometric applications.

Original languageEnglish
Title of host publicationIEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010
DOIs
StatePublished - Dec 27 2010
Event4th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010 - Washington, DC, United States
Duration: Sep 27 2010Sep 29 2010

Other

Other4th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010
CountryUnited States
CityWashington, DC
Period9/27/109/29/10

Fingerprint

Biometrics
Histogram
Object recognition
Support vector machines
Feature extraction
Classifiers
Detectors
3D Object Recognition
Shape Feature
Sliding Window
False Positive
Feature Extraction
Efficacy
Support Vector Machine
Simplicity
Classifier
Detector
Three-dimensional
Experimental Results
Range of data

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Zhou, J., Cadavid, S., & Abdel-Mottaleb, M. (2010). Histograms of categorized shapes for 3D ear detection. In IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010 [5634512] https://doi.org/10.1109/BTAS.2010.5634512

Histograms of categorized shapes for 3D ear detection. / Zhou, Jindan; Cadavid, Steven; Abdel-Mottaleb, Mohamed.

IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010. 2010. 5634512.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, J, Cadavid, S & Abdel-Mottaleb, M 2010, Histograms of categorized shapes for 3D ear detection. in IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010., 5634512, 4th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010, Washington, DC, United States, 9/27/10. https://doi.org/10.1109/BTAS.2010.5634512
Zhou J, Cadavid S, Abdel-Mottaleb M. Histograms of categorized shapes for 3D ear detection. In IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010. 2010. 5634512 https://doi.org/10.1109/BTAS.2010.5634512
Zhou, Jindan ; Cadavid, Steven ; Abdel-Mottaleb, Mohamed. / Histograms of categorized shapes for 3D ear detection. IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010. 2010.
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