Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking

Abstract

The paper proposes a diversity-enhanced condensation algorithm to address the particle impoverishment problem which stochastic filtering usually suffers from. The particle diversity plays an important role as it affects the performance of filtering. Although the condensation algorithm is widely used in computer vision, it easily gets trapped in local minima due to the particle degeneracy. We introduce a modified evolutionary computing method, adaptive differential evolution, to resolve the particle impoverishment under a proper size of particle population. We apply our proposed method to endoscope tracking for estimating three-dimensional motion of the endoscopic camera. The experimental results demonstrate that our proposed method offers more robust and accurate tracking than previous methods. The current tracking smoothness and error were significantly reduced from (3.7, 4.8) to (2.3 mm, 3.2 mm), which approximates the clinical requirement of 3.0 mm.

Cite

Text

Luo et al. "Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.163

Markdown

[Luo et al. "Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/luo2014cvpr-diversityenhanced/) doi:10.1109/CVPR.2014.163

BibTeX

@inproceedings{luo2014cvpr-diversityenhanced,
  title     = {{Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking}},
  author    = {Luo, Xiongbiao and Wan, Ying and He, Xiangjian and Yang, Jie and Mori, Kensaku},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.163},
  url       = {https://mlanthology.org/cvpr/2014/luo2014cvpr-diversityenhanced/}
}