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).
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Böhme, M., Haker, M., Riemer, K., Martinetz, T., Barth, E. (2009). Face Detection Using a Time-of-Flight Camera. In: Kolb, A., Koch, R. (eds) Dynamic 3D Imaging. Dyn3D 2009. Lecture Notes in Computer Science, vol 5742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03778-8_13
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DOI: https://doi.org/10.1007/978-3-642-03778-8_13
Publisher Name: Springer, Berlin, Heidelberg
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