Dynamic Vergence Using Log-Polar Images

摘要

Vergence provides robot vision systems with a crucial degree of freedom: it enables fixation of points in visual space at different distances from the observer. Vergence control, therefore, affects the performance of the stereo system as well as the results of motion estimation and tracking and, as such, must satisfy different requirements in order to be able to provide not only a stable fixation, but a stable binocular fusion, and a fast, smooth and accurate reaction to changes in the environment. To obtain this kind of performance the paper focuses specifically on the use of dynamic visual information to drive vergence control. In this context, moreover, the use of a space-variant, anthropomorphic sensor is described and some advantages in relation to vergence control are discussed to demonstrate the relevance of image plane geometry for this particular task. Expansion or contraction patterns and the temporal evolution of the degree of fusion measured in the log-polar domain are the inputs to the vergence control system and determine robust and accurate steering of the two cameras. Real-time experiments are presented to demonstrate the performance of the system covering different key situations.