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» Markov Random Field Modeling in Computer Vision
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CVPR
2010
IEEE
14 years 5 months ago
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
CVPR
2012
IEEE
11 years 11 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller
ICIP
2005
IEEE
14 years 10 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang
ANOR
2010
139views more  ANOR 2010»
13 years 7 months ago
Some operations research methods for analyzing protein sequences and structures
Operations Research is probably one of the most successful fields of applied mathematics used in Economics, Physics, Chemistry, almost everywhere onehastoanalyzehugeamountsofdata.L...
Piotr Lukasiak, Jacek Blazewicz, Maciej Milostan
WWW
2007
ACM
14 years 9 months ago
Netprobe: a fast and scalable system for fraud detection in online auction networks
Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implemen...
Shashank Pandit, Duen Horng Chau, Samuel Wang, Chr...