The capacity to recognize faces under varied poses is a fundamental human ability that
presents a unique challenge for computer vision systems. Compared to frontal face …

As one of the most successful applications of image analysis and understanding, face
recognition has recently received significant attention, especially during the past several …

Abstract In 2007, Labeled Faces in the Wild was released in an effort to spur research in
face recognition, specifically for the problem of face verification with unconstrained images …

Most face databases have been created under controlled conditions to facilitate the study of
specific parameters on the face recognition problem. These parameters include such …

We present a generative appearance-based method for recognizing human faces under
variation in lighting and viewpoint. Our method exploits the fact that the set of images of an …

Over the past three decades or so, research on machine learning and data mining has led to
a wide variety of algorithms that learn general functions from experience. As machine …

We set ourselves the task of recognizing persons from single images by reference to a
gallery, which also contained only one image per person. Our problem was to address …

This paper presents a method for face recognition across variations in pose, ranging from
frontal to profile views, and across a wide range of illuminations, including cast shadows and …

This paper describes the automatic selection of features from an image training set using the
theories of multidimensional discriminant analysis and the associated optimal linear …

This paper investigates learning in a lifelong context. Lifelong learning addresses situations
in which a learner faces a whole stream of learn (cid: 173) ing tasks. Such scenarios provide …