Dynamic Vergence Using Log-Polar Images
International Journal of Computer Vision
Robot Vision
Disparity estimation on log-polar images and vergence control
Computer Vision and Image Understanding
Vergence Control and Disparity Estimation with Energy Neurons: Theory and Implementation
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic assessment of disparity vergence ramps
Computers in Biology and Medicine
Version and vergence control of a stereo camera head by fitting the movement into the Hering's law
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
Stability analysis and design of a class of MIMO fuzzy control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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An important issue in realizing robots with stereo vision is the efficient control of the vergence angle. In an active robotic vision system the vergence angle along with the pan and tilt ones determines uniquely the fixation point in the 3D space. The vergence control involves the adjustment of the angle between the two cameras’ axes towards the fixation point and, therefore, it enables the robot to perceive depth and to compute obstacle maps. Vergence movement is directly related to the binocular fusion. Additionally, the decision for convergence or divergence is extracted either by motion affine models or by mathematical ones. In this paper, a new method for extracting the cameras’ movement direction is presented. The movement decision is performed by an adaptive fuzzy control system, the inputs of which are the zero-mean normalized cross correlation (ZNCC) and the depth estimations at each time step. The proposed system is assessed on a 4 d.o.f. robotic head, yet it can be utilized in any active binocular system, since it is computationally inexpensive and it is independent to a priori camera calibration.