Scale-Invariant Range Features for Time-of-Flight Camera Applications
Abstract
We describe a technique for computing scale-invariant features on range maps produced by a range sensor, such as a time-of-flight camera. Scale invariance is achieved by computing the features on the reconstructed three-dimensional surface of the object. The technique is general and can be applied to a wide range of operators. Features are computed in the frequency domain; the transform from the irregularly sampled mesh to the frequency domain uses the Nonequispaced Fast Fourier Transform. We demonstrate the technique on a facial feature detection task. On a dataset containing faces at various distances from the camera, the equal error rate (EER) for the case of scale-invariant features is halved compared to features computed on the range map in the conventional way. When the scale-invariant range features are combined with intensity features, the error rate on the test set reduces to zero.
Cite
Text
Haker et al. "Scale-Invariant Range Features for Time-of-Flight Camera Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563169Markdown
[Haker et al. "Scale-Invariant Range Features for Time-of-Flight Camera Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/haker2008cvprw-scaleinvariant/) doi:10.1109/CVPRW.2008.4563169BibTeX
@inproceedings{haker2008cvprw-scaleinvariant,
title = {{Scale-Invariant Range Features for Time-of-Flight Camera Applications}},
author = {Haker, Martin and Böhme, Martin and Martinetz, Thomas and Barth, Erhardt},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2008},
pages = {1-6},
doi = {10.1109/CVPRW.2008.4563169},
url = {https://mlanthology.org/cvprw/2008/haker2008cvprw-scaleinvariant/}
}