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» Hybrid Hierarchical Learning from Dynamic Scenes
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CVPR
2010
IEEE
14 years 3 months ago
Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes
A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique ut...
Shandong Wu, Brian E. Moore, and Mubarak Shah
PAMI
2006
233views more  PAMI 2006»
13 years 7 months ago
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
This paper sets out a tracking framework, which is applied to the recovery of threedimensional hand motion from an image sequence. The method handles the issues of initialization,...
Björn Stenger, Arasanathan Thayananthan, Phil...
PAMI
2006
193views more  PAMI 2006»
13 years 7 months ago
A System for Learning Statistical Motion Patterns
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, w...
Weiming Hu, Xuejuan Xiao, Zhouyu Fu, Dan Xie, Tien...
WAPCV
2007
Springer
14 years 1 months ago
Language Label Learning for Visual Concepts Discovered from Video Sequences
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Prithwijit Guha, Amitabha Mukerjee
DAGSTUHL
2007
13 years 9 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...