Emergence and Categorization of Coordinated Visual Behavior ThroughEmbodied Interaction
Machine Learning - Special issue on learning in autonomous robots
A Humanoid Vision System for Versatile Interaction
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
MAP ZDF segmentation and tracking using active stereo vision: Hand tracking case study
Computer Vision and Image Understanding
Pipelined architecture for real-time cost-optimized extraction of visual primitives based on FPGAs
Digital Signal Processing
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We have designed and implemented a real-time binocular tracking system which uses two independent cues commonly found in the primary functions of biological visual systems to robustly track moving targets in complex environments, without a-priori knowledge of the target shape or texture: a fast optical flow segmentation algorithm quickly locates independently moving objects for target acquisition and provides a reliable velocity estimate for smooth tracking. In parallel, target position is generated from the output of a zero-disparity filter where a phase-based disparity estimation technique allows dynamic control of the camera vergence to adapt the horopter geometry to the target location. The system takes advantage of the optical properties of our custom-designed foveated wide-angle lenses, which exhibit a wide field of view along with a high resolution fovea. Methods to cope with the distortions introduced by the space-variant resolution, and a robust real-time implementation on a high performance active vision head are presented.