Perceiving Heading in the Presence of Moving Objects

TLDR

Heading perception from optic flow typically assumes a rigid environment, but humans often navigate with independently moving objects, and simple spatial pooling of flow can produce systematic heading errors. The study used a simulated observer translating toward a random‑dot plane while a 10‑degree square moved independently in depth, varying its path to create a secondary focus of expansion 6° from the true heading, and modeled the data with a large‑field, center‑weighted expansion template. When the moving object occluded the true focus of expansion, perceived heading was biased toward the secondary focus by about 1.9° for a transparent object and 3.4° for an opaque one, indicating that scene segmentation does not precede heading estimation and that spatial pooling near the focus may be an adaptive navigation strategy.

Abstract

In most models of heading from optic flow a rigid environment is assumed, yet humans often navigate in the presence of independently moving objects. Simple spatial pooling of the flow field would yield systematic heading errors. Alternatively, moving objects could be segmented on the basis of relative motion, dynamic occlusion, or inconsistency with the global flow, and heading determined from the background flow. Displays simulated observer translation toward a frontal random-dot plane, with a 10 deg square moving independently in depth. The path of motion of the object was varied to create a secondary focus of expansion (FOE') 6 deg to the right or left of the actual heading point (FOE), which could bias the perceived heading. There was no effect when the FOE was visible, but when the object moved in front of it, perceived heading was biased toward the FOE' by ∼1.9° with a transparent object, and ∼3.4° with an opaque object. The results indicate that scene segmentation does not occur prior to heading estimation, which is consistent with spatial pooling weighted near the FOE. A simple template model based on large-field, center-weighted expansion units accounts for the data. This may actually represent an adaptive solution for navigation with respect to obstacles on the path ahead.