Face Detection Using a Time-of-Flight Camera

Authors:
Martin Böhme;Martin Haker;Kolja Riemer;Thomas Martinetz;Erhardt Barth
Affiliations:
Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany D-23538;Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany D-23538;Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany D-23538;Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany D-23538;Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany D-23538
Venue:
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
Year:
2009

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Abstract

We adapt the well-known face detection algorithm of Viola and Jones to work on the range and intensity data from a time-of-flight camera. The detector trained on the combined data has a higher detection rate (95.3%) than detectors trained on either type of data alone (intensity: 93.8%, range: 91.2%). Additionally, the combined detector uses fewer image features and hence has a shorter running time (5.15 ms per frame) than the detectors trained on intensity or range individually (intensity: 10.69 ms, range: 5.51 ms).