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» Gaussian Process Dynamical Models for Human Motion
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ICIP
2004
IEEE
16 years 1 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
ICPR
2008
IEEE
15 years 6 months ago
Adaptive local contrast enhancement for the visualization of high dynamic range images
In this paper, we present a new tone mapping algorithm for the display of high dynamic range images, inspired by adaptive process of the human visual system. The proposed algorith...
Jian Zhang, Sei-ichiro Kamata
ICMCS
2006
IEEE
191views Multimedia» more  ICMCS 2006»
15 years 6 months ago
Human Vision System Aware Exhaustive Block-Matching Algorithm
In this work, homomorphic image modeling is used to make the exhaustive block-matching algorithm (EBMA) more human vision system (HVS) aware, thus yielding visually pleasing seque...
David Lin, Paul Chau
IJCV
1998
163views more  IJCV 1998»
14 years 11 months ago
CONDENSATION - Conditional Density Propagation for Visual Tracking
The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot repre...
Michael Isard, Andrew Blake
ICIAP
2001
Springer
16 years 3 hour ago
Recognition of Shape-Changing Hand Gestures Based on Switching Linear Model
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...