Real-Time Tracking Using Level Sets

Abstract

In this paper we propose a novel implementation of the level set method that achieves real-time level-set-based video tracking. In our fast algorithm, the evolution of the curve is realized by simple operations such as switching elements between two linked lists and there is no need to solve any partial differential equations. Furthermore, a novel procedure based on Gaussian filtering is introduced to incorporate boundary smoothness regularization. By replacing the standard curve length penalty with this new smoothing procedure, further speedups are obtained. Another advantage of our fast algorithm is that the topology of the curves can be controlled easily. For the tracking of multiple objects, we extend our fast algorithm to maintain the desired topology for multiple object boundaries based on ideas from discrete topology. With our fast algorithm, a real-time system has been implemented on a standard PC and only a small fraction of the CPU power is used for tracking. Results from standard test sequences and our realtime system are presented.

Cite

Text

Shi and Karl. "Real-Time Tracking Using Level Sets." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.294

Markdown

[Shi and Karl. "Real-Time Tracking Using Level Sets." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/shi2005cvpr-real/) doi:10.1109/CVPR.2005.294

BibTeX

@inproceedings{shi2005cvpr-real,
  title     = {{Real-Time Tracking Using Level Sets}},
  author    = {Shi, Yonggang and Karl, William Clement},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2005},
  pages     = {34-41},
  doi       = {10.1109/CVPR.2005.294},
  url       = {https://mlanthology.org/cvpr/2005/shi2005cvpr-real/}
}