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» Graph-Theoretical Methods in Computer Vision
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ECCV
2006
Springer
16 years 8 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
CVPR
2010
IEEE
16 years 3 months ago
Action Unit Detection with Segment-based SVMs
Automatic facial action unit (AU) detection from video is a long-standing problem in computer vision. Two main approaches have been pursued: (1) static modeling--typically posed a...
Tomas Simon, Nguyen Minh, Fernando De la Torre, Je...
ICPR
2010
IEEE
15 years 5 months ago
Scene-Adaptive Human Detection with Incremental Active Learning
In many computer vision tasks, scene changes hinder the generalization ability of trained classifiers. For instance, a human detector trained with one set of images is unlikely t...
Ajay Joshi, Fatih Porikli
ICCV
2011
IEEE
14 years 6 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
199
Voted
ICIAP
2009
ACM
16 years 7 months ago
Real-Time Online Video Object Silhouette Extraction Using Graph Cuts on the GPU
Abstract. Being able to find the silhouette of an object is a very important front-end processing step for many high-level computer vision techniques, such as Shape-from-Silhouette...
Zachary A. Garrett, Hideo Saito