Active Tracking Strategy for Monocular Depth Inference over Multiple Frames
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time binocular smooth pursuit
International Journal of Computer Vision
Active tracking of foveated feature clusters using affine structure
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Active Vision from Multiple Cues
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
International Journal of Computer Vision
Efficient active monocular fixation using the log-polar sensor
International Journal of Intelligent Systems Technologies and Applications
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
Real-time visuomotor update of an active binocular head
Autonomous Robots
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This paper presents a general approach for the simultaneous tracking of multiple moving targets using a generic active stereo setup. The problem is formulated on the plane, where cameras are modeled as "line scan cameras," and targets are described as points with unconstrained motion. We propose to control the active system parameters in such a manner that the images of the targets in the two views are related by a homography. This homography is specified during the design stage and, thus, can be used to implicitly encode the desired tracking behavior. Such formulation leads to an elegant geometric framework that enables a systematic and thorough analysis of the problem at hand. The benefits of the approach are illustrated by applying the framework to two distinct stereo configurations. In the first case, we assume two pan-tilt-zoom cameras, with rotation and zoom control, which are arbitrarily placed in the working environment. It is proved that such a stereo setup can track up to N = 3 free-moving targets, while assuring that the image location of each target is the same for both views. The second example considers a robot head with neck pan motion and independent eye rotation. For this case, it is shown that it is not possible to track more than N = 2 targets because of the lack of zoom. The theoretical framework is used to derive the control equations, and the implementation of the tracking behavior is described in detail. The correctness of the results is confirmed through simulations and real tracking experiments.