Visually guided vergence in a new stereo camera system

  • Adam Schneider
  • Namrata Sharma
  • Bryan Tripp

Abstract

People move their eyes several times each second, to selectively
analyze visual information from specific locations. This is impor-
tant, because analyzing the whole scene in foveal detail would re-
quire a beachball-sized brain and thousands of additional calories
per day. As artificial vision becomes more sophisticated, it may
face analogous constraints. Anticipating this, we previously devel-
oped a robotic head with biologically realistic oculomotor capabil-
ities. Here we present a system for accurately orienting the cam-
eras toward a three-dimensional point. The robot’s cameras con-
verge when looking at something nearby, so each camera should
ideally centre the same visual feature. At the end of a saccade,
we combine priors with cross-correlation of the images from each
camera to iteratively fine-tune their alignment, and we use the ori-
entations to set focus distance. This system allows the robot to
accurately view a visual target with both eyes.

Published
2018-12-24
How to Cite
Schneider, A., Sharma, N., & Tripp, B. (2018). Visually guided vergence in a new stereo camera system. Journal of Computational Vision and Imaging Systems, 4(1), 3. Retrieved from https://openjournals.uwaterloo.ca/index.php/vsl/article/view/344