Look where you go: characterizing eye movements toward optic flow

When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the pattern’s focus of expansion (Knöll, Pillow & Huk, 2018). Here we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers, and how eye movements are affected by motion signal strength and task instructions. Observers (n = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: saccades landed closer to the focus of expansion and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts.

Vision-Based Obstacle Avoidance Strategies for MAVs Using Optical Flows in 3-D Textured Environments

Due to payload restrictions for micro aerial vehicles (MAVs), vision-based approaches have been widely studied with their light weight characteristics and cost effectiveness. In particular, optical flow-based obstacle avoidance has proven to be one of the most efficient methods in terms of obstacle avoidance capabilities and computational load; however, existing approaches do not consider 3-D complex environments. In addition, most approaches are unable to deal with situations where there are wall-like frontal obstacles. Although some algorithms consider wall-like frontal obstacles, they cause a jitter or unnecessary motion. To address these limitations, this paper proposes a vision-based obstacle avoidance algorithm for MAVs using the optical flow in 3-D textured environments. The image obtained from a monocular camera is first split into two horizontal and vertical half planes. The desired heading direction and climb rate are then determined by comparing the sum of optical flows between half planes horizontally and vertically, respectively, for obstacle avoidance in 3-D environments. Besides, the proposed approach is capable of avoiding wall-like frontal obstacles by considering the divergence of the optical flow at the focus of expansion and navigating to the goal position using a sigmoid weighting function. The performance of the proposed algorithm was validated through numerical simulations and indoor flight experiments in various situations.

Artificial Optic Flow Guides Visual Attention in a Driving Scene

Objective The objective of this study was to investigate whether an artificial optic flow created by dot motion guides attention in a driving scene. Background To achieve safe driving, it is essential to understand the characteristics of human visual information processing as well as to provide appropriate support for drivers. Past research has demonstrated that expanding optic flow guides visual attention to the focus of expansion. Optic flow is an attractive candidate for use as a cue to direct drivers’ attention toward the significant information. The question addressed concerns whether an artificial optic flow can successfully guide attention even in a traffic situation involving the optic flow that naturally occurs while driving. Method We developed a visual search paradigm embedded in a video of a driving scene. Participants first observed an optic flow motion pattern superimposed on the video for brief period; next, when the optic flow and video ceased, they searched a static display for a target among multiple distractors. Results The target detection was faster when a target’s locus coincided with the implied focus of expansion from the preceding optic flow (vs. other loci). Conclusion The artificial optic flow guides attention and facilitates searching objects at the focus of expansion even when the optic flow was superimposed on a driving scene. Application Optic flow can be an effective cue for guiding drivers’ attention in a traffic situation. This finding contributes to the understanding of visual attention in moving space and helps develop technology for traffic safety.

A new road tracking method based on heading direction detection

Current research on road tracking is mostly based on the visual perception of road boundaries. In this paper, we propose a novel and general road tracker based on optical flow computation, which can be applied to most of road environments including the case of a lack of lane markings or road boundaries. When the heading direction of the vehicle and the road direction are identical, the focus of expansion (FOE) coincides with the road vanishing point (RVP). This is an important foundation for the subsequent heading direction departure decision. By comparing the relative positions of the estimated FOE and RVP, we can learn the traveling state of the vehicle. The experimental results show that the proposed tracker is a simple and efficient road tracking method.

Differential processing of the direction and focus of expansion of optic flow stimuli in areas MST and V3A of the human visual cortex

Human neuropsychological and neuroimaging studies have raised the possibility that different attributes of optic flow stimuli, namely radial direction and the position of the focus of expansion (FOE), are processed within separate cortical areas. In the human brain, visual areas V5/MT+ and V3A have been proposed as integral to the analysis of these different attributes of optic flow stimuli. To establish direct causal relationships between neural activity in human (h)V5/MT+ and V3A and the perception of radial motion direction and FOE position, we used transcranial magnetic stimulation (TMS) to disrupt cortical activity in these areas while participants performed behavioral tasks dependent on these different aspects of optic flow stimuli. The cortical regions of interest were identified in seven human participants using standard functional MRI retinotopic mapping techniques and functional localizers. TMS to area V3A was found to disrupt FOE positional judgments but not radial direction discrimination, whereas the application of TMS to an anterior subdivision of hV5/MT+, MST/TO-2 produced the reverse effects, disrupting radial direction discrimination but eliciting no effect on the FOE positional judgment task. This double dissociation demonstrates that FOE position and radial direction of optic flow stimuli are signaled independently by neural activity in areas hV5/MT+ and V3A. NEW & NOTEWORTHY Optic flow constitutes a biologically relevant visual cue as we move through any environment. With the use of neuroimaging and brain-stimulation techniques, this study demonstrates that separate human brain areas are involved in the analysis of the direction of radial motion and the focus of expansion in optic flow. This dissociation reveals the existence of separate processing pathways for the analysis of different attributes of optic flow that are important for the guidance of self-locomotion and object avoidance.