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» Learning to Track with Multiple Observers
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CVPR
2003
IEEE
14 years 1 months ago
Continuous Tracking Within and Across Camera Streams
This paper presents a new approach for continuous tracking of moving objects observed by multiple, heterogeneous cameras. Our approach simultaneously processes video streams from ...
Jinman Kang, Isaac Cohen, Gérard G. Medioni
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 7 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
ICML
2004
IEEE
14 years 8 months ago
A multiplicative up-propagation algorithm
We present a generalization of the nonnegative matrix factorization (NMF), where a multilayer generative network with nonnegative weights is used to approximate the observed nonne...
Jong-Hoon Ahn, Seungjin Choi, Jong-Hoon Oh
TIP
2008
157views more  TIP 2008»
13 years 7 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji
ICML
2009
IEEE
14 years 8 months ago
More generality in efficient multiple kernel learning
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Manik Varma, Bodla Rakesh Babu