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PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 4 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
ECCV
2004
Springer
15 years 12 months ago
A Bayesian Framework for Multi-cue 3D Object Tracking
This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linea...
Jan Giebel, Dariu Gavrila, Christoph Schnörr
TMM
2008
167views more  TMM 2008»
14 years 10 months ago
Mining Appearance Models Directly From Compressed Video
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
Datong Chen, Qiang Liu, Mingui Sun, Jie Yang
WWW
2009
ACM
15 years 10 months ago
Learning to tag
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, a...
Lei Wu, Linjun Yang, Nenghai Yu, Xian-Sheng Hua
CA
1999
IEEE
15 years 2 months ago
Fast Synthetic Vision, Memory, and Learning Models for Virtual Humans
This paper presents a simple and efficient method of modeling synthetic vision, memory, and learning for autonomous animated characters in real-time virtual environments. The mode...
James J. Kuffner Jr., Jean-Claude Latombe