TY - CONF T1 - Evaluation of state-of-the-art algorithms for remote face recognition T2 - Image Processing (ICIP), 2010 17th IEEE International Conference on Y1 - 2010 A1 - Ni,Jie A1 - Chellapa, Rama KW - alarm;feature KW - algorithm;still KW - classification;image KW - classification;visual KW - database;remote KW - databases; KW - extraction;hidden KW - extraction;image KW - Face KW - feature KW - image-based KW - image;false KW - quality;occlusion;remote KW - recognition;face KW - recognition;feature KW - recognition;state-of-the-art KW - removal;image AB - In this paper, we describe a remote face database which has been acquired in an unconstrained outdoor environment. The face images in this database suffer from variations due to blur, poor illumination, pose, and occlusion. It is well known that many state-of-the-art still image-based face recognition algorithms work well, when constrained (frontal, well illuminated, high-resolution, sharp, and complete) face images are presented. In this paper, we evaluate the effectiveness of a subset of existing still image-based face recognition algorithms for the remote face data set. We demonstrate that in addition to applying a good classification algorithm, consistent detection of faces with fewer false alarms and finding features that are robust to variations mentioned above are very important for remote face recognition. Also setting up a comprehensive metric to evaluate the quality of face images is necessary in order to reject images that are of low quality. JA - Image Processing (ICIP), 2010 17th IEEE International Conference on M3 - 10.1109/ICIP.2010.5652608 ER -