Head tracking using stereo

Authors:
Daniel B. Russakoff;Martin Herman
Affiliations:
National Institute of Standards and Technology, 100 Bureau Drive, Stop 8940, Gaithersburg, MD;National Institute of Standards and Technology, 100 Bureau Drive, Stop 8940, Gaithersburg, MD
Venue:
Machine Vision and Applications - Special issue: IEEE WACV
Year:
2002

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Abstract

Head tracking is an important primitive for smart environments and perceptual user interfaces where the poses and movements of body parts need to be determined. Most prevaous solutions to this problem are based on intensity images and, as a result, suffer from a host of problems including sensitivity to background clutter and lighting variations. Our approach avoids these pitfalls by using stereo depth data together with a simple human-torso model to create a head-tracking system that is both fast and robust. We use stereo data1 to derive a depth model of the background that is then employed to provide accurate foreground segmentation. We then use directed local edge detectors on the foreground to find occluding edges that are used as features to fit to a torso model. Once we have the model parameters, the location and orientation of the head can be easily estimated. A useful side effect from using stereo data is the ability to track head movement through a room in three dimensions. Experimental results on real image sequences are given.