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» Algorithmic Fusion for More Robust Feature Tracking
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CVPR
2012
IEEE
13 years 2 days ago
Robust object tracking via sparsity-based collaborative model
In this paper we propose a robust object tracking algorithm using a collaborative model. As the main challenge for object tracking is to account for drastic appearance change, we ...
Wei Zhong, Huchuan Lu, Ming-Hsuan Yang
IJRR
2006
183views more  IJRR 2006»
14 years 9 months ago
Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application
Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today's system...
Christophe Coué, Cédric Pradalier, C...
AIRS
2006
Springer
15 years 1 months ago
A Semantic Fusion Approach Between Medical Images and Reports Using UMLS
One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first...
Daniel Racoceanu, Caroline Lacoste, Roxana Teodore...
IROS
2006
IEEE
151views Robotics» more  IROS 2006»
15 years 3 months ago
Robust Feature Correspondences for Vision-Based Navigation with Slow Frame-Rate Cameras
— We propose a vision-based inertial system that overcomes the problems associated with slow update rates in navigation systems based on high-resolution cameras. Due to bandwidth...
Darius Burschka
ICCV
2007
IEEE
15 years 11 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 ...