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» Multi-feature Graph-Based Object Tracking
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ICCV
2007
IEEE
14 years 6 months ago
Probabilistic Color and Adaptive Multi-Feature Tracking with Dynamically Switched Priority Between Cues
We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
François Le Clerc, Lionel Oisel, Patrick P&...
ICCV
2007
IEEE
14 years 6 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
CLEAR
2006
Springer
133views Biometrics» more  CLEAR 2006»
13 years 8 months ago
Multi-feature Graph-Based Object Tracking
We present an object detection and tracking algorithm that addresses the problem of multiple simultaneous targets tracking in realworld surveillance scenarios. The algorithm is bas...
Murtaza Taj, Emilio Maggio, Andrea Cavallaro
GBRPR
2005
Springer
13 years 10 months ago
A Graph-Based, Multi-resolution Algorithm for Tracking Objects in Presence of Occlusions
One of the main difficult problem in video analysis is to track moving objects during a video sequence, especially in presence of occlusions. Unfortunately, almost all the differ...
Donatello Conte, Pasquale Foggia, Jean-Michel Joli...
ICPR
2008
IEEE
13 years 11 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock