Depth Camera Tracking with Contour Cues

CVPR 2015

doi:10.1109/CVPR.2015.7298662 /cvpr/2015/zhou2015cvpr-depth/

Abstract

We present an approach for tracking camera pose in real time given a stream of depth images. Existing algorithms are prone to drift in the presence of smooth surfaces that destabilize geometric alignment. We show that useful contour cues can be extracted from noisy and incomplete depth input. These cues are used to establish correspondence constraints that carry information about scene geometry and constrain pose estimation. Despite ambiguities in the input, the presented contour constraints reliably improve tracking accuracy. Results on benchmark sequences and on additional challenging examples demonstrate the utility of contour cues for real-time camera pose estimation.

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Cite

Text

Zhou and Koltun. "Depth Camera Tracking with Contour Cues." Conference on Computer Vision and Pattern Recognition, 2015. doi:10.1109/CVPR.2015.7298662

Markdown

[Zhou and Koltun. "Depth Camera Tracking with Contour Cues." Conference on Computer Vision and Pattern Recognition, 2015.](https://mlanthology.org/cvpr/2015/zhou2015cvpr-depth/) doi:10.1109/CVPR.2015.7298662

BibTeX

@inproceedings{zhou2015cvpr-depth,
  title     = {{Depth Camera Tracking with Contour Cues}},
  author    = {Zhou, Qian-Yi and Koltun, Vladlen},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2015},
  doi       = {10.1109/CVPR.2015.7298662},
  url       = {https://mlanthology.org/cvpr/2015/zhou2015cvpr-depth/}
}