A major unsolved problem in computer graphics is the construction and animation of realistic human facial models. Traditionally, facial models have been built painstakingly by manual digitization and animated by ad hoc parametrically controlled facial mesh deformations or kinematic approximation

of 50,000 images. The data consists of 3D scans and high resolution still imagery taken under controlled and uncontrolled conditions. This paper describes the challenge problem, data corpus, and presents baseline performance and preliminary results on natural statistics of facial imagery. 1.

Face recognition has benefitted greatly from the many databases that have been produced to study it. Most of these databases have been created under controlled conditions to facilitate the study of specific parameters on the face recognition problem. These parameters include such variables

Abstract Behavioral countermeasures are the strategies engaged by liars to deliberately control face or body behavior to fool lie catchers. To date research has not shown whether deceivers can suppress elements of their facial expression as a behavioral countermeasure. This study examined whether

Frames from a voice-driven animation, computed from a single baby picture and an adult model of facial control. Note the changes in upper facial expression. See figures 5, 6 and 7 for more examples of predicted mouth shapes. We introduce a method for predicting a control signal from another related

an estimation technique that uses deformable contour models (snakes) to track the nonrigid motions of facial features in video images. The technique estimates muscle actuator controls with sufficient accuracy to permit the face model to resynthesize transient expressions.

In this experiment, we combined the measurement of observable facial behavior with simultaneous measures of brain electrical ctivity to assess patterns of hemispheric a tivation i different regions during the experience ofhappiness and disgust. Disgust was found to be associated with right

relatives. One candidate cue of relatedness in humans is facial resemblance. Here, I report the effects of an experimental manipulation of facial resemblance in a two-person sequential trust game. Subjects were shown faces of ostensible playing partners manipulated to resemble either themselves

experienced increased attention recently. Most current research focuses on techniques for capturing, synthesizing, and retargeting facial expressions. Little attention has been paid to the problem of controlling and modifiing the expression itself. We present techniques that separate video data

. The class of simple models considered are those formed as the sum of a few atoms from some (possibly infinite) elementary atomic set; examples include well-studied cases such as sparse vectors (e.g., signal processing, statistics) and low-rank matrices (e.g., control, statistics), as well as several others