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A complementary local feature descriptor for face identification

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4 Author(s)
Jonghyun Choi ; Inst. for Adv. Comput. Studies, Univ. of Maryland, College Park, MD, USA ; Schwartz, W.R. ; Huimin Guo ; Davis, L.S.

In many descriptors, spatial intensity transforms are often packed into a histogram or encoded into binary strings to be insensitive to local misalignment and compact. Discriminative information, however, might be lost during the process as a trade-off. To capture the lost pixel-wise local information, we propose a new feature descriptor, Circular Center Symmetric-Pairs of Pixels (CCS-POP). It concatenates the symmetric pixel differences centered at a pixel position along various orientations with various radii; it is a generalized form of Local Binary Patterns, its variants and Pairs-of-Pixels (POP). Combining CCS-POP with existing descriptors achieves better face identification performance on FRGC Ver. 1.0 and FERET datasets compared to state-of-the-art approaches.

Published in:

Applications of Computer Vision (WACV), 2012 IEEE Workshop on

Date of Conference:

9-11 Jan. 2012