We address the problem of automatically learning object models for recognition and pose estimation. In contrast to the traditional approach, we formulate the recognition problem a...
We present a new approach to iteratively estimate both
high-quality depth map and alpha matte from a single image
or a video sequence. Scene depth, which is invariant
to illumin...
Jiejie Zhu (University of Kentucky), Miao Liao (Un...
Parametric models of shape and texture such as Active Appearance Models (AAMs) are diverse tools for deformable object appearance modeling and have found important applications in...
?We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training ...
Timothy F. Cootes, Gareth J. Edwards, Christopher ...
We investigate the task of 2D articulated human pose estimation in unconstrained still images. This is extremely challenging because of variation in pose, anatomy, clothing, and i...