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» Novel Observation Model for Probabilistic Object Tracking
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ICPR
2008
IEEE
14 years 3 months ago
Top down image segmentation using congealing and graph-cut
This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
AVSS
2005
IEEE
14 years 2 months ago
Scene modelling using an adaptive mixture of Gaussians in colour and space
We present an integrated pixel segmentation and region tracking algorithm, designed for indoor environments. Visual monitoring systems often use frame differencing techniques to i...
Patrick Dickinson, Andrew Hunter
ICCV
1998
IEEE
14 years 11 months ago
Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
Existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. In some situations ...
Tony Heap, David Hogg
ICPR
2004
IEEE
14 years 10 months ago
A Fast Discriminant Approach to Active Object Recognition and Pose Estimation
This paper presents a new criterion for viewpoint selection in the context of active Bayesian object recognition and pose estimation. Recognition is performed by probabilistically...
Catherine Laporte, Rupert Brooks, Tal Arbel
ICIP
2007
IEEE
14 years 10 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro