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ICML
2002
IEEE
16 years 7 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
ICCV
2009
IEEE
16 years 11 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
CVPR
2003
IEEE
16 years 8 months ago
Using Multiple Cues for Hand Tracking and Model Refinement
We present a model based approach to the integration of multiple cues for tracking high degree of freedom articulated motions and model refinement. We then apply it to the problem...
Shan Lu, Dimitris N. Metaxas, Dimitris Samaras, Jo...
CVPR
2004
IEEE
16 years 8 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
ECCV
2006
Springer
15 years 10 months ago
Tracking of Multiple Objects Using Optical Flow Based Multiscale Elastic Matching
Abstract. A novel hybrid region-based and contour-based multiple object tracking model using optical flow based elastic matching is proposed. The proposed elastic matching model is...
Xingzhi Luo, Suchendra M. Bhandarkar