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Human posture recognition for intelligent vehicles

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Abstract

Pedestrian detection systems are finding their way into many modern “intelligent” vehicles. The body posture could reveal further insight about the pedestrian’s intent and her awareness of the oncoming car. This article details the algorithms and implementation of a library for real-time body posture recognition. It requires prior person detection and then calculates overall stance, torso orientation in four increments, and head location and orientation, all based on individual frames. A syntactic post-processing module takes temporal information into account and smoothes the results over time while correcting improbable configurations. We show accuracy and timing measurements for the library and its utilization in a training application.

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Acknowledgments

This research was supported by a grant from the Office of Naval Research and it was performed while the first author held a National Research Council Research Associateship Award at the Naval Postgraduate School.

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Authors and Affiliations

  1. School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Juan P. Wachs

  2. MOVES Institute, Naval Postgraduate School, Monterey, CA, USA

    Mathias Kölsch & Deborah Goshorn

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  1. Juan P. Wachs
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  2. Mathias Kölsch
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  3. Deborah Goshorn
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Correspondence to Juan P. Wachs.

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Wachs, J.P., Kölsch, M. & Goshorn, D. Human posture recognition for intelligent vehicles. J Real-Time Image Proc 5, 231–244 (2010). https://doi.org/10.1007/s11554-010-0150-0

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