Multiple Collaborative Kernel Tracking
Abstract
This paper presents a novel multiple collaborative kernel approach to visual tracking. This approach treats kernel-based tracking in a more general setting, i.e., a relaxation and constraints formulation, in which a complex motion is represented by a set of inter-correlated simpler motions. With this formulation, we present a rigorous analysis on a critical issue of kernel observability and obtain a criterion, based on which we propose a new method using collaborative kernels that has the theoretical guarantee of enhanced observability. This new method has been shown to be computationally efficient in both theory and practice, which can be readily applied to complex motions such as articulated motions.
Cite
Text
Fan et al. "Multiple Collaborative Kernel Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.242Markdown
[Fan et al. "Multiple Collaborative Kernel Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/fan2005cvpr-multiple/) doi:10.1109/CVPR.2005.242BibTeX
@inproceedings{fan2005cvpr-multiple,
title = {{Multiple Collaborative Kernel Tracking}},
author = {Fan, Zhimin and Wu, Ying and Yang, Ming},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2005},
pages = {502-509},
doi = {10.1109/CVPR.2005.242},
url = {https://mlanthology.org/cvpr/2005/fan2005cvpr-multiple/}
}