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Real-Time Head Detection with Kinect for Driving Fatigue Detection

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Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8228))

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Abstract

Nowadays, depth cameras such Microsoft Kinect make it easier and cheaper for us to capture depth images. It becomes practical to use depth images for detection in consumer-grade products. In this paper, we propose a novel and simple real-time method to detect human head in depth image for our driving fatigue detection system, based on the elliptical shape of human head. Experiments show that our method can successfully detect human head in different light conditions and across different head poses. We integrate this detection algorithm into our driving fatigue detection system, and see remarkable improvements both in detection rate and detection speed.

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Cao, Y., Lu, BL. (2013). Real-Time Head Detection with Kinect for Driving Fatigue Detection. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_74

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  • DOI: https://doi.org/10.1007/978-3-642-42051-1_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42050-4

  • Online ISBN: 978-3-642-42051-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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