TY - GEN
T1 - Adaptive appearance based face recognition
AU - Li, Qi
AU - Ye, Jieping
AU - Li, Min
AU - Kambhamettu, Chandra
PY - 2006
Y1 - 2006
N2 - In this paper, we present an adaptive appearance based face recognition framework that combines the efficiency of global approaches and the robustness of local approaches together. The framework uses a novel eye locator to select an appropriate scheme for appearance based recognition. The eye locator first locates eye candidates via a new strength assignment, determined by the dissimilarity between the local appearance of an image point and the appearance of its neighboring points. Then the eye locator applies a simple but flexible model (half-circle snake) to the local context of the eye candidates in order to either refine the location of an eye candidate or discard non-eye candidates. We show the performance of our framework by testing on challenging face datasets containing extreme expressions, severe occlusions, and varied lighting conditions.
AB - In this paper, we present an adaptive appearance based face recognition framework that combines the efficiency of global approaches and the robustness of local approaches together. The framework uses a novel eye locator to select an appropriate scheme for appearance based recognition. The eye locator first locates eye candidates via a new strength assignment, determined by the dissimilarity between the local appearance of an image point and the appearance of its neighboring points. Then the eye locator applies a simple but flexible model (half-circle snake) to the local context of the eye candidates in order to either refine the location of an eye candidate or discard non-eye candidates. We show the performance of our framework by testing on challenging face datasets containing extreme expressions, severe occlusions, and varied lighting conditions.
UR - http://www.scopus.com/inward/record.url?scp=38949104805&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=38949104805&partnerID=8YFLogxK
U2 - 10.1109/ICTAI.2006.25
DO - 10.1109/ICTAI.2006.25
M3 - Conference contribution
AN - SCOPUS:38949104805
SN - 0769527280
SN - 9780769527284
T3 - Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
SP - 677
EP - 684
BT - Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006
T2 - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006
Y2 - 13 October 2006 through 15 October 2006
ER -