Gaze stabilization in active vision--I. Vergence error extraction

Abstract This paper discusses the problems associated with purposeful gazing and fixation of attention for systems with active vision. To help bridge the gap between our current standpoint in active gazing and where advantages that holding gaze brings, we propose solution to the important problems involved in gaze stabilization, i.e. vergence error extraction, and vergence servo control. In the first part, we focus on vergence error extraction. In the next paper, ‘Gaze Stabilization in Active Vision II: Multi-rate Vergence Control’, we shall focus on vergence control. Binocular gazing is realized by decreasing the disparity which represents the vergence error. In order to obtain the disparity for extraction of vergence error, a phase-based approach that efficiently estimates vergence disparity is developed. Experiments are conducted to investigate the effects of window size, segmentation techniques, and illumination.

[1]  Peter J. Burt,et al.  Smart sensing within a pyramid vision machine , 1988, Proc. IEEE.

[2]  Hiroshi Ishiguro,et al.  Acquiring 3D structure by controlling visual attention of a mobile robot , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[3]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[4]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[5]  A.L. Abbott,et al.  A survey of selective fixation control for machine vision , 1992, IEEE Control Systems.

[6]  C.M. Brown,et al.  Cooperative gaze holding in binocular vision , 1991, IEEE Control Systems.

[7]  James J. Clark,et al.  Modal Control Of An Attentive Vision System , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[8]  Ramesh C. Jain,et al.  Detecting time-varying corners , 1984, Comput. Vis. Graph. Image Process..

[9]  John K. Tsotsos,et al.  Techniques for disparity measurement , 1991, CVGIP Image Underst..

[10]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[11]  Yehezkel Yeshurun,et al.  Cepstral Filtering on a Columnar Image Architecture: A Fast Algorithm for Binocular Stereo Segmentation , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  D. Vleeschauwer An intensity-based, coarse-to-fine approach to reliably measure binocular disparity , 1993 .

[13]  Alfred M. Bruckstein,et al.  A new method for image segmentation , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[14]  Mansur R. Kabuka,et al.  Robot vision tracking system , 1988 .

[15]  Michael Werman,et al.  Active vision: 3D from an image sequence , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[16]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[17]  Eric Paul Krotkov,et al.  Active Computer Vision by Cooperative Focus and Stereo , 1989, Springer Series in Perception Engineering.

[18]  N. Ranganathan,et al.  Corner detection , 1990, Pattern Recognit..

[19]  Azriel Rosenfeld,et al.  Gray-level corner detection , 1982, Pattern Recognit. Lett..

[20]  C. Chow,et al.  Automatic boundary detection of the left ventricle from cineangiograms. , 1972, Computers and biomedical research, an international journal.

[21]  A. Lynn Abbott,et al.  Active Stereo: Integrating Disparity, Vergence, Focus, Aperture and Calibration for Surface Estimation , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  R. Bajcsy Active perception , 1988 .