Exploiting distinctive visual landmark maps in pan-tilt-zoom camera networks
Computer Vision and Image Understanding
An experimental framework for evaluating PTZ tracking algorithms
ICVS'11 Proceedings of the 8th international conference on Computer vision systems
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This paper considers the problem of estimating on-line the time-variant transformation relating a person's feet position in the image of a first, fixed camera, to his head position in the image of a second, pan-tilt-zoom camera. The transformation allows to acquire high-resolution images by steering the PTZ camera at targets detected in a fixed camera view. Assuming a planar scene and modeling humans as vertical segments, we present the development of an uncalibrated framework which does not require any 3D known location to be specified, and it allows to take into account both zooming camera and target uncertainties. Results show good performances in slave camera target head localization, degrading when the high zoom factor causes a lack of feature points in the slave camera.