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» Learning Enhanced 3D Models for Vehicle Tracking
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ECCV
2002
Springer
15 years 11 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
AMDO
2006
Springer
15 years 1 months ago
Combined Head, Lips, Eyebrows, and Eyelids Tracking Using Adaptive Appearance Models
The ability to detect and track human heads and faces in video sequences is useful in a great number of applications, such as human-computer interaction and gesture recognition. Re...
Fadi Dornaika, Javier Orozco, Jordi Gonzàle...
CVPR
1997
IEEE
15 years 11 months ago
Stereo Coupled Active Contours
We consider how tracking in stereo may be enhanced by coupling pairs of active contours in different views via affine epipolar geometry and various subsets of planar affine transf...
Tat-Jen Cham, Roberto Cipolla
AAAI
2012
13 years 11 hour ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke
CVPR
2007
IEEE
15 years 11 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic