CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We present an automated method for the tracking and dynamics modeling of microtubules -a major component of the cytoskeleton- which provides researchers with a previously unattain...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We describe a realtime system for finding and tracking unstructured paths in off-road conditions. The system was designed as part of the recent Darpa Grand Challenge and was teste...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We develop a novel technique for measuring lighting that exploits the interaction of light with a set of custom BRDFs. This enables the construction of a planar light probe with c...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We study the epipolar geometry between views acquired by mixtures of central projection systems including catadioptric sensors and cameras with lens distortion. Since the projecti...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We present a novel multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in detect...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using...
CVPR
2006
IEEE
15 years 4 days ago
2006
IEEE
We propose a new technique for edge-suppressing operations on images. We introduce cross projection tensors to achieve affine transformations of gradient fields. We use these tens...