CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM t...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We introduce an epitomic representation for modeling human activities in video sequences. A video sequence is divided into segments within which the dynamics of objects is assumed...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
While face recognition techniques have rapidly advanced in the last few years, most of the work is in the domain of security applications. For consumer imaging applications, perso...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We present DIGITABLE, an experimental platform we hope lessen the gap between co-present and distant interaction. DIGITABLE is combining a multiuser tactile interactive tabletop, ...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We propose a framework for detecting and tracking multiple interacting objects, while explicitly handling the dual problems of fragmentation (an object may be broken into several ...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Many vision tasks are posed as either graph partitioning (coloring) or graph matching (correspondence) problems. The former include segmentation and grouping, and the latter inclu...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper, we develop a discriminative framework for simultaneous se...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
In this paper, we address two closely related visual tracking problems: 1) localizing a target's position in low or moderate resolution videos and 2) segmenting a target'...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We present spectral matting: a new approach to natural image matting that automatically computes a set of fundamental fuzzy matting components from the smallest eigenvectors of a ...