
Proceedings Paper
Robust face recognition algorithm for identifition of disaster victimsFormat | Member Price | Non-Member Price |
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Paper Abstract
We present a robust face recognition algorithm for the identification of occluded, injured and mutilated faces
with a limited training set per person. In such cases, the conventional face recognition methods fall short due to
specific aspects in the classification. The proposed algorithm involves recursive Principle Component Analysis
for reconstruction of afiected facial parts, followed by a feature extractor based on Gabor wavelets and uniform
multi-scale Local Binary Patterns. As a classifier, a Radial Basis Neural Network is employed. In terms of
robustness to facial abnormalities, tests show that the proposed algorithm outperforms conventional face recognition
algorithms like, the Eigenfaces approach, Local Binary Patterns and the Gabor magnitude method. To
mimic real-life conditions in which the algorithm would have to operate, specific databases have been constructed
and merged with partial existing databases and jointly compiled. Experiments on these particular databases
show that the proposed algorithm achieves recognition rates beyond 95%.
Paper Details
Date Published: 19 February 2013
PDF: 11 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 865503 (19 February 2013); doi: 10.1117/12.2001634
Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)
PDF: 11 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 865503 (19 February 2013); doi: 10.1117/12.2001634
Show Author Affiliations
Wouter J. R. Gevaert, Technische Univ. Eindhoven (Netherlands)
Peter H. N. de With, Technische Univ. Eindhoven (Netherlands)
Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)
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