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» A Framework for Implicitly Tracking Data
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ICML
2004
IEEE
14 years 8 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
AAAI
2010
13 years 9 months ago
A Bayesian Nonparametric Approach to Modeling Mobility Patterns
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...
HT
2010
ACM
13 years 9 months ago
Assessing users' interactions for clustering web documents: a pragmatic approach
In this paper we are interested in describing Web pages by how users interact within their contents. Thus, an alternate but complementary way of labelling and classifying Web docu...
Luis A. Leiva, Enrique Vidal
CVPR
2007
IEEE
14 years 9 months ago
Multimodal Tracking for Smart Videoconferencing and Video Surveillance
Many applications require the ability to track the 3-D motion of the subjects. We build a particle filter based framework for multimodal tracking using multiple cameras and multip...
Dmitry N. Zotkin, Vikas C. Raykar, Ramani Duraiswa...
FGR
2008
IEEE
192views Biometrics» more  FGR 2008»
13 years 8 months ago
Tracking a walking person using activity-guided annealed particle filtering
Tracking human pose using observations from less than three cameras is a challenging task due to ambiguity in the available image evidence. This work presents a method for trackin...
John Darby, Baihua Li, Nicholas Costen