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» Modeling and Learning Contact Dynamics in Human Motion
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FGCN
2008
IEEE
175views Communications» more  FGCN 2008»
14 years 2 months ago
Environment Recognition Based on Human Actions Using Probability Networks
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
Hiroshi Miki, Atsuhiro Kojima, Koichi Kise
CVPR
2010
IEEE
14 years 4 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
CSIE
2009
IEEE
14 years 2 months ago
Discriminative Random Fields for Behavior Modeling
This paper proposed an approach of human behavior modeling based on Discriminative Random Fields. In this model, by introducing the hidden behavior feature functions and time wind...
Tianyu Huang, Chongde Shi, Fengxia Li
ATAL
2006
Springer
13 years 11 months ago
Multi-model motion tracking under multiple team member actuators
Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
Yang Gu, Manuela M. Veloso
ICIP
2007
IEEE
13 years 12 months ago
Real-Time Pedestrian Detection using Eigenflow
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
Dhiraj Goel, Tsuhan Chen