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» Incremental Learning for Robust Visual Tracking
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CVPR
2009
IEEE
16 years 4 months ago
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates
We propose a space-time Markov Random Field (MRF) model to detect abnormal activities in video. The nodes in the MRF graph correspond to a grid of local regions in the video fra...
Jaechul Kim (University of Texas at Austin), Krist...
IROS
2009
IEEE
195views Robotics» more  IROS 2009»
15 years 4 months ago
Appearance contrast for fast, robust trail-following
— We describe a framework for finding and tracking “trails” for autonomous outdoor robot navigation. Through a combination of visual cues and ladar-derived structural inform...
Christopher Rasmussen, Yan Lu, Mehmet Kocamaz
CVPR
2009
IEEE
16 years 4 months ago
Learning Visual Flows: A Lie Algebraic Approach
We present a novel method for modeling dynamic visual phenomena, which consists of two key aspects. First, the in- tegral motion of constituent elements in a dynamic scene is ca...
Dahua Lin, W. Eric L. Grimson, John W. Fisher III
83
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ICIC
2005
Springer
15 years 2 months ago
Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
CORR
2000
Springer
84views Education» more  CORR 2000»
14 years 9 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett