Adaptive pyramid mean shift for global real-time visual tracking
Image and Vision Computing
Visual object tracking by an evolutionary self-organizing neural network
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
Evolving a self-organizing feature map for visual object tracking
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Tracking multiple feature in infrared image with mean-shift
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Hi-index | 0.01 |
In this paper, we propose a novel decision fusion algorithm for target tracking in forward-looking infrared image sequences recorded from an airborne platform. An important part of this study is identifying the failure modes in this type of imagery. Our strategy is to prevent these failure modes from developing into tracking failures. The results furnished by competing ego-motion compensation and tracking algorithms are evaluated based on their similarity to a target model constructed using the weighted composite reference function.