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ICML
2007
IEEE
14 years 7 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
CVPR
2008
IEEE
14 years 9 months ago
Visual tracking via incremental Log-Euclidean Riemannian subspace learning
Recently, a novel Log-Euclidean Riemannian metric [28] is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means ...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
ACCV
2007
Springer
14 years 1 months ago
Depth from Stationary Blur with Adaptive Filtering
This work achieves an efficient acquisition of scenes and their depths along long streets. A camera is mounted on a vehicle moving along a path and a sampling line properly set in ...
Jiang Yu Zheng, Min Shi
TOG
2012
297views Communications» more  TOG 2012»
11 years 9 months ago
Adaptive manifolds for real-time high-dimensional filtering
We present a technique for performing high-dimensional filtering of images and videos in real time. Our approach produces high-quality results and accelerates filtering by compu...
Eduardo S. L. Gastal, Manuel M. Oliveira
ICCV
2009
IEEE
13 years 4 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu