Paper
26 January 2009 Automatic human detecting and tracking using stereo vision technique
Author Affiliations +
Proceedings Volume 7238, The Engineering Reality of Virtual Reality 2009; 723803 (2009) https://doi.org/10.1117/12.806066
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
A fully automatic system for human detection and tracking in front of an Interactive Whiteboard is presented. When a person is between a projector and the projection area, deleterious effects can be created from light shining on the face. We developed a stereo vision system that can be used to mitigate problems arising from this issue by accurately detecting the human body and masking the face. We present two main parts of this system: namely, automatic system calibration and the human detection and tracking. We use a checkerboard pattern that is projected on the whiteboard at start-up for automatic calibration. Grid patterns from two images are processed, and points between them are detected and localized. A projective transform is used to set the homography between the two images. Testing shows precise automatic calibration, with an average RMS error of 0.4 pixels in the off-line test. Human detection and tracking is accomplished using a similarity measure, foreground segmentation, principle component analysis, body shape feature extraction, disparity measure, and location estimation. We achieved an average detection rate of 97.7 % in the off-line tests. The method was fully implemented in a real-time system and testing showed the system to be very robust.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yunqiu Wang and Gerald Morrison "Automatic human detecting and tracking using stereo vision technique", Proc. SPIE 7238, The Engineering Reality of Virtual Reality 2009, 723803 (26 January 2009); https://doi.org/10.1117/12.806066
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KEYWORDS
Head

Image segmentation

Calibration

Cameras

Automatic tracking

Hough transforms

Stereo vision systems

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