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» Adaptive Background Estimation for Object Tracking
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SSIAI
2000
IEEE
15 years 1 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
FGR
1998
IEEE
131views Biometrics» more  FGR 1998»
15 years 1 months ago
Tracking and Segmenting People in Varying Lighting Conditions Using Colour
Colour cues were used to obtain robust detection and tracking of people in relatively unconstrained dynamic scenes. Gaussian mixture models were used to estimate probability densi...
Yogesh Raja, Stephen J. McKenna, Shaogang Gong
88
Voted
ICIP
2008
IEEE
15 years 3 months ago
Level set tracking with dynamical shape priors
Dynamical shape priors are curical for level set-based nonrigid object tracking with noise, occlusions or background clutter. In this paper, we propose a level set tracking framew...
Xue Zhou, Xi Li, Weiming Hu
PAMI
2010
162views more  PAMI 2010»
14 years 4 months ago
Differential Earth Mover's Distance with Its Applications to Visual Tracking
The Earth Mover's Distance (EMD) is a similarity measure that captures perceptual difference between two distributions. Its computational complexity, however, prevents a direc...
Qi Zhao, Zhi Yang, Hai Tao
AMFG
2003
IEEE
163views Biometrics» more  AMFG 2003»
15 years 2 months ago
Pose Estimation using 3D View-Based Eigenspaces
In this paper we present a method for estimating the absolute pose of a rigid object based on intensity and depth viewbased eigenspaces, built across multiple views of example obj...
Louis-Philippe Morency, Patrik Sundberg, Trevor Da...