Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensio...
Leonid Sigal, Michael Isard, Benjamin H. Sigelman,...
Many applications, ranging from visualization applications such as architectural walkthroughs to robotic applications such as surveillance, could benefit from an automatic camera ...
This paper presents an online system which is capable of reconstructing and rendering dynamic objects in real scenes. We reconstruct visual hulls of the objects by using a shape-f...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...