... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition,

We present a novel 3D face recognition approach based on geometric invariants introduced by Elad and Kimmel. The key idea of the proposed algorithm is a representation of the facial surface, invariant to isometric deformations, such as those resulting from different expressions and postures of the face. The obtained geometric invariants allow mapping 2D facial texture images into special images that incorporate the 3D geometry of the face. These signature images are then decomposed into their principal components. The result is an efficient and accurate face recognition algorithm that is robust to facial expressions. We demonstrate the results of our method and compare it to existing 2D and 3D face recognition algorithms.

This survey compares internal representations of the recent as well as more traditional face recognition techniques to classify them into several broad categories. The categories assessed include template matching and feature measurements, analysis of global and local facial features, and incorporation of interpersonal and intrapersonal variations of human faces. Analysis of the face recognition systems within those broad categories makes it possible to identify strong and weak sides of each group of methods. The paper argues that a fruitful direction for future research may lie in weighing information about facial features together with localized image features in order to provide a better mechanism for

This paper addresses 3D face recognition from facial shape. Firstly, we present an effective method to automatically extract ROI of facial surface, which mainly depends on automatic detection of facial bilateral symmetry plane and localization of nose tip. Then we build a reference plane through the nose tip for calculating the relative depth values. Considering the non-rigid property of facial surface, the ROI is triangulated and parameterized into an isomorphic 2D planar circle, attempting to preserve the intrinsic geometric properties. At the same time the relative depth values are also mapped. Finally we perform eigenface on the mapped relative depth image. The entire scheme is insensitive to pose variance. The experiment using FRGC database v1.0 obtains the rank-1 identification score of 95%, which outperforms the result of the PCA base-line method by 4%, which demonstrates the effectiveness of our algorithm. 1

Abstract. Many researches in face recognition have been dealing with the challenge of the great variability in head pose, lighting intensity and direction,facial expression, and aging. The main purpose of this overview is to describe the recent 3D face recognition algorithms. The last few years more and more 2D face recognition algorithms are improved and tested on less than perfect images. However, 3D models hold more information of the face, like surface information, that can be used for face recognition or subject discrimination. Another major advantage is that 3D face recognition is pose invariant. A disadvantage of most presented 3D face recognition methods is that they still treat the human face as a rigid object. This means that the methods aren’t capable of handling facial expressions. Although 2D face recognition still seems to outperform the 3D face recognition methods, it is expected that this will change in the near future. 1

Abstract not found

this paper: 1) a correlation-based method, 2) a variant of the linear subspace method suggested in [150], 3) an eigenface method [173], and 4) a Fisherface method which uses subspace projection prior to LDA projection to avoid the possible singularity in Sw as in [166]. The results of the experiments showed that the Fisherface method performed significantly better than the other three methods. However, no claim was made about the relative performance of these algorithms on larger databases

Abstract—Recently, a 3D face recognition approach based on geometric invariant signatures, has been proposed. The key idea of the algorithm is a representation of the facial surface, invariant to isometric deformations, such as those resulting from facial expressions. One of the crucial stages in the construction of the geometric invariants is the measurement of geodesic distances on triangulated surfaces, carried out by fast marching on triangulated domains (FMTD). Proposed here is a method, which uses only the metric tensor of the surface for geodesic distance computation. When combined with photometric stereo used for facial surface acquisition, it allows constructing a bendinginvariant representation of the face without reconstructing the 3D surface. Index Terms--face recognition, fast marching, photometric stereo, multidimensional scaling.

by mathematics and recalls spending "hours just roaming around, sometimes working mathematics problems mentally" (Bledsoe 1976). When Woody was 12, his father died. It was a devastating blow both emotionally and financially. As Woody recalled, "We were poor before, but after papa died in January 1934, things got worse" (Bledsoe 1976). He and the rest of his brothers and sisters worked dreary 10-hour days to make ends meet. Woody ran away from home at 16. He found work in north Texas driving a tractor all night. After a month, he hopped a freight train to Colorado to visit his brother, who was working in a Civilian Conservation Corps camp. After a few weeks, he made his way to the south Texas town of Calliham, where he lived with some friends for a year. He graduated from high school during that year (1939). Woody then returned to live with his mother, who had moved to Norman, Oklahoma. He took a job as a dishwasher, working 12-hour days 7 days a week. He enrolled at the University o

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past few years. This is evidenced by the emergence of face-recognition conferences such asAFGR [7] andAVBPA[9] and many commercially available systems. There are