In this paper, a novel framework for face recognition, namely Selective Ensemble of Image Regions (SEIR), is proposed. In this framework, all possible regions in the face image are...
In this paper, we introduce a new system for 3-D face recognition based on the fusion of results from a committee of regions that have been independently matched. Experimental resu...
Timothy C. Faltemier, Kevin W. Bowyer, Patrick J. ...
We propose a learning framework that actively explores creation of face space(s) by selecting images that are complementary to the images already represented in the face space. We...
Abstract. In human face recognition, different facial regions have different degrees of importance, and exploiting such information would hopefully improve the accuracy of the reco...
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...