Temporal thresholds for feature detection in flow visualization

Abstract

Optic flow is the coherent motion of a region in the visual field, and the visual system is astoundingly effective at perceiving this large-scale and complex percept. Whenever you rotate your head or move through a scene, nearly every part of your visual field moves at a different speed and velocity. For example, as you walk through a forest, the trees in the horizon appear to slowly expand, and the trees on your sides appear to rapidly move to the extremities of your vision visual field and disappear. In spite of such a myriad of local motions, all of this information is concisely summarized as moving forward. Such summary encoding of a large variety of elements makes this percept a potentially useful tool to exploit for visualization. For that reason, our goal in this study is to test the visual system's ability to use optic flow for a basic visualization task, feature detection.