Abstract
A head tracking system for automatically detecting and tracking human heads in complex backgrounds is developed. In this paper, two issues are addressed: the detection of human heads and the development of a head tracking system. First, based on an elliptical model for the human head, we propose a Maximum Likelihood (ML) detector to reliably locate human heads in images having complex backgrounds. This ellipse-based ML head detector is relatively insensitive to illumination and rotation of the human heads, and its computation is similar to template matching. Second, we develop a head tracking system that can monitor the entrance of a person, detect and track the person's head, and then control the stereo cameras to focus their gaze on this person's head. Difference images are used to detect the entrance of a human. The ellipse-based ML head detector and the mutually-supported constraint are used to extract the corresponding ellipses in a stereo image pair. Then, the 3D position computed from the centers of the two corresponding ellipses can be used for fixation. A well-calibrated active stereo head, the IIS-head, is used to perform the experiments and demonstrate that our approach is feasible and promising.
This work was partially supported by National Science Council of Taiwan under grant NSC 86-2745-E-001-007.
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© 1997 Springer-Verlag Berlin Heidelberg
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Tang, CY., Hung, YP., Chen, Z. (1997). Automatic detection and tracking of human heads using an active stereo vision system. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63930-6_176
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DOI: https://doi.org/10.1007/3-540-63930-6_176
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