Bauer S, Wasza J, Müller K, Hornegger J (2011)
Publication Type: Conference contribution, Conference Contribution
Publication year: 2011
Original Authors: Bauer S., Wasza J., Müller K., Hornegger J.
Book Volume: null
Pages Range: 196-203
Event location: Kona, HI
Journal Issue: null
DOI: 10.1109/WACV.2011.5711503
Methods for 2D/3D face recognition typically combine results obtained independently from the 2D and 3D data, respectively. There has not been much emphasis on data fusion at an early stage, even though it is at least potentially more powerful to exploit possible synergies between the two modalities. In this paper, we propose photogeometric features that interpret both the photometric texture and geometric shape information of 2D manifolds in a consistent manner. The 4D features encode the spatial distribution of gradients that are derived generically for any scalar field on arbitrary organized surface meshes. We apply the descriptor for biometric face recognition with a time-of-flight sensor. The method consists of three stages: (i) facial landmark localization with a HOG/SVM sliding window framework, (ii) extraction of photogeometric feature descriptors from time-of-flight data, using the inherent grayscale intensity information of the sensor as the 2D manifold's scalar field, (iii) probe matching against the gallery. Recognition based on the photogeometric features achieved 97.5% rank-1 identification rate on a comprehensive time-of-flight dataset (26 subjects, 364 facial images). © 2010 IEEE.
APA:
Bauer, S., Wasza, J., Müller, K., & Hornegger, J. (2011). 4D photogeometric face recognition with time-of-flight sensors. In Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011 (pp. 196-203). Kona, HI.
MLA:
Bauer, Sebastian, et al. "4D photogeometric face recognition with time-of-flight sensors." Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011, Kona, HI 2011. 196-203.
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