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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-6
Martin Bohme , Institute for Neuro- and Bioinformatics, University of Lübeck Ratzeburger Allee 160, 23538, Germany
Thomas Martinetz , Institute for Neuro- and Bioinformatics, University of Lübeck Ratzeburger Allee 160, 23538, Germany
Erhardt Barth , Institute for Neuro- and Bioinformatics, University of Lübeck Ratzeburger Allee 160, 23538, Germany
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.
CITATION
Martin Bohme, Thomas Martinetz, Erhardt Barth, "Scale-invariant range features for time-of-flight camera applications", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-6, doi:10.1109/CVPRW.2008.4563169
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