Simulating the detection of first-order optical flow components.

Thresholds for the detection of rotation and divergence in the presence of a translational component in sparse random dot patterns are determined for human observers and two computer algorithms. The algorithms only make use of local velocity directions and not of local velocity magnitude (speed). The results show that psychophysical performance in this task can be well described without the need of specialized mechanisms tuned to either rotation or divergence. Possibly, integration of information over more than two frames occurs for low velocities. For high velocities the correspondence problem seems to limit performance.