We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Understanding neural connectivity and structures in the brain requires detailed 3D anatomical models, and such an understanding is essential to the study of the nervous system. Ho...
In this paper, we introduce a new system for profilebased face recognition. The specific scenario involves a driver entering a gated area and using his/her sideview image (the dri...
Ioannis A. Kakadiaris, H. Abdelmunim, W. Yang, The...
Active Appearance Models (AAMs) have been popularly used to represent the appearance and shape variations of human faces. Fitting an AAM to images recovers the face pose as well a...
We propose a simplified and practical computational technique for estimating directional lighting in uncalibrated images of faces in frontal pose. We show that this inverse probl...