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» Integration of Background Modeling and Object Tracking
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ICCV
2011
IEEE
13 years 10 months ago
Superpixel Tracking
While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion,...
Shu Wang, Huchuan Lu, Fan Yang, Ming-Hsuan Yang
ROBOCUP
2007
Springer
208views Robotics» more  ROBOCUP 2007»
15 years 4 months ago
3D Tracking by Catadioptric Vision Based on Particle Filters
This paper presents a robust tracking system for autonomous robots equipped with omnidirectional cameras. The proposed method uses a 3D shape and color-based object model. This all...
Matteo Taiana, José António Gaspar, ...
ICASSP
2007
IEEE
15 years 5 months ago
Speeded Up Gradient Vector Flow B-Spline Active Contours for Robust and Real-Time Tracking
Segmentation and tracking methods have been widely explore. However, they are often computationally heavy or require constraining assumptions. We present in this paper a new syste...
Joanna I. Olszewska, Christophe De Vleeschouwer, B...
CVPR
1999
IEEE
16 years 20 days ago
Object Recognition with Color Cooccurrence Histograms
We use the color cooccurrence histogram (CH) for recognizing objects in images. The color CH keeps track of the number of pairs of certain colored pixels that occur at certain sep...
Peng Chang, John Krumm
IJCV
2008
188views more  IJCV 2008»
14 years 10 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin