We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
We propose a method for segmentation of frontal human portraits from arbitrary unknown backgrounds. Semantic information is used to project the face into a normalized reference fr...
David C. Schneider, Benjamin Prestele, Peter Eiser...
We present new techniques for creating photorealistic textured 3D facial models from photographs of a human subject, and for creating smooth transitions between different facial e...
Frederic H. Pighin, Jamie Hecker, Dani Lischinski,...
We propose a fast 3D model acquisition system that aligns intensity and depth images, and reconstructs a textured 3D mesh. 3D views are registered with shape alignment based on in...
Louis-Philippe Morency, Ali Rahimi, Trevor Darrell
We face the question of how to produce a scale space of image intensities relative to a scale space of objects or other characteristic image regions filling up the image space, whe...
Stephen M. Pizer, Ja-Yeon Jeong, Robert E. Broadhu...