期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 21, 期 1, 页码 305-315出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2011.2160957
关键词
Bias-variance tradeoff; face recognition; LASSO regression; pose differences; ridge regression
资金
- DoD Counterdrug Technology Development Program Office
- Natural Science Foundation of China [60833013, U0835005]
- National Basic Research Program of China [2009CB320902]
Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.
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