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» Learning Low-Level Vision
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ICCV
2001
IEEE
14 years 10 months ago
Stochastic Processes in Vision: From Langevin to Beltrami
Diffusion processes which are widely used in low level vision are presented as a result of an underlying stochastic process. The short-time non-linear diffusion is interpreted as ...
Nir A. Sochen
ECCV
2000
Springer
14 years 10 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...
MVA
2000
161views Computer Vision» more  MVA 2000»
13 years 10 months ago
Vision Based Global Navigation System for Autonomous Urban Transport Vehicles in Outdoor Partially Known Environments
This paper describes a vision-based system for autonomous urban transport missions in outdoor environments. Specialized modules are implemented for particular tasks such as lane t...
Miguel Ángel Sotelo Vázquez, Luis Ma...
CVPR
2007
IEEE
14 years 10 months ago
Detecting Pedestrians by Learning Shapelet Features
In this paper, we address the problem of detecting pedestrians in still images. We introduce an algorithm for learning shapelet features, a set of mid?level features. These featur...
Payam Sabzmeydani, Greg Mori
ICPR
2008
IEEE
14 years 3 months ago
Intuitive event modeling for personalized behavior monitoring
Behavior understanding and semantic interpretation of dynamic visual scenes have attracted a lot of attention in computer vision research community. Although the use of surveillan...
Ahmed Azough, Alexandre Delteil, Fabien De Marchi,...