Perceiving Heading in the Presence of Moving Objects

Warren, William H.; Saunders, Jeffrey A.

doi:10.1068/p240315

Cited by 146 publications

(265 citation statements)

References 35 publications

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“…Cutting et al (1995) have suggested that we look near our path at stationary obstacles, in part, for the purposes ofavoiding them and of updating information about heading direction; we look at moving obstacles only for the purpose of avoidance because information about heading direction seems poor under conditions of pursuit fixation (but see W. H. Warren & Saunders, 1995;Royden & Hildreth, 1996). In this article, we focus on looking at stationary obstacles.…”

Section: Pursuit Fixation During Gaitmentioning

confidence: 99%

Heading and path information from retinal flow in naturalistic environments

Cutting

Vishton

Flückiger

et al. 1997

Perception & Psychophysics

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In four experiments, we explored the heading and path information available to observers as we simulated their locomotion through a cluttered environment while they fixated an object off to the side. Previously, we presented a theory about the information available and used in such situations. For such a theory to be valid, one must be sure of eye position, but we had been unable to monitor gaze systematically; in Experiment I, we monitored eye position and found performance best when observers fixated the designated object at the center of the display. In Experiment 2, when we masked portions of the display, we found that performance generally matched the amount of display visible when scaled to retinal sensitivity. In Experiments 3 and 4, we then explored the metric of information about heading (nominal vs. absolute) available and found good nominal information but increasingly poor and biased absolute information as observers looked farther from the aimpoint. Part of the cause for this appears to be that some observers perceive that they have traversed a curved path even when taking a linear one. In all cases, we compared our results with those in the literature.How do we negotiate cluttered environments during our daily activities? How is it that we can generally do this with relative ease and without injury? What information subserves the determination of our direction ofmovement, often called heading? For over a decade, we have been developing a theory of wayfinding based on the use of particular sources of information in retinal flow, the complex of motion and displacement information projected to the retina of an individual moving through a rigid environment while fixating an object somewhat offhis or her path (Cutting, 1986(Cutting, , 1996Cutting, Springer, Braren, & Johnson, 1992; Cutting, Vishton, & Braren, 1995;. Strategically, we have simulated naturalistic environments relatively rich in sources of information about layout-occlusion, relative size, relative density, height in the visual field, in addition to motion perspective.'We thank

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Section: Pursuit Fixation During Gaitmentioning

confidence: 99%

Heading and path information from retinal flow in naturalistic environments

Cutting

Vishton

Flückiger

et al. 1997

Perception & Psychophysics

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“…Although early studies of heading perception assumed a static environment, real world navigational situations usually involve the traversal of environments containing stationary and moving objects. The presence of independently moving objects in the optic flow field has been shown to impair heading judgment only when the object moves across the direction of travel, obscuring the veridical focus of expansion (Warren & Saunders, 1995;Royden & Hildreth, 1996). Subjects can also tolerate significant amounts of velocity noise in the optic flow display, suggesting that heading perception primarily relies on the directional pattern of motion in the optic flow field (Warren, Blackwell, Kurtz, Hatsopoulos, & Kalish, 1991).…”

Section: Introductionmentioning

confidence: 99%

A neural model of visually guided steering, obstacle avoidance, and route selection.

Elder¹,

Grossberg²,

Mingolla³

2009

Journal of Experimental Psychology: Human Perception and Perfor

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A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Key Words: Heading Perception, Steering, Optic Flow, Obstacle, Goal, Pursuit Eye Movement, Gain Fields, Peak Shift, V2, MT, MST, VIP, LIP 3 IntroductionMany important steering tasks are guided by visual information, including walking through a cluttered environment (Fajen & Warren, 2003), driving (Land & Horwood, 1995;Hildreth, Beusmans, Boer, & Royden, 2000;Wallis, Chatziastros, & Bülthoff, 2002), vehicle braking (Lee, 1976, piloting an aircraft (Gibson, Olum, & Rosenblatt, 1955;Beall & Loomis, 1997), and intercepting a moving target on foot (Fajen & Warren, 2004). Steering through a cluttered environment involves the selection of a path that avoids obstacles and simultaneously approaches the intended goal. Human steering is guided by visual information about the spatial layout of the environment and the direction of self-motion through the environment, as well as proprioceptive feedback and information from other sensory systems. In particular, the visual system provides information about the relative positions of the goal object and obstacles in the environment.Movement through the world creates a full-field pattern of motion on the retina, called optic flow, which contains information about the direction of self-motion, or heading (Gibson, 1950). In principle, optic flow can be used to compute heading (Longuet-Higgins & Prazdny, 1980). During translational movement of the eye, the optic flow field contains a singularity, called the focus of expansion, which specifies the direction of heading in the absence of an eye rotation.Figures 1 & 2 Whereas optic flow relates observer motion to the available visual stimuli, recent research clarifies how visual information governs the dynamics of human navigational behavior. Fajen and Warren (2003) studied the dynamics of human steering behavior in simple goal approach and obstacle avoidance tasks using an immersive virtual reality system. They found that human performa...

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“…Visual information such as optic flow can be used to judge heading under certain conditions (Gibson, 1950;Warren, 2003). However, vision alone is often insufficient because the retinal image is confounded by changes in gaze or by motion of objects in the visual field (Royden et al, 1992Royden, 1994;Warren and Saunders, 1995;Banks et al, 1996;Royden and Hildreth, 1996;Crowell et al, 1998). A possible solution may be to combine visual information with inertial signals that specify the motion of the head in space, such as from the vestibular otolith organs (Fernandez and Goldberg, 1976).…”

Section: Introductionmentioning

confidence: 99%

Spatial Reference Frames of Visual, Vestibular, and Multimodal Heading Signals in the Dorsal Subdivision of the Medial Superior Temporal Area

Fetsch¹,

Wang²,

Gu³

et al. 2007

J. Neurosci.

119

122

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Heading perception is a complex task that generally requires the integration of visual and vestibular cues. This sensory integration is complicated by the fact that these two modalities encode motion in distinct spatial reference frames (visual, eye-centered; vestibular, head-centered). Visual and vestibular heading signals converge in the primate dorsal subdivision of the medial superior temporal area (MSTd), a region thought to contribute to heading perception, but the reference frames of these signals remain unknown. We measured the heading tuning of MSTd neurons by presenting optic flow (visual condition), inertial motion (vestibular condition), or a congruent combination of both cues (combined condition). Static eye position was varied from trial to trial to determine the reference frame of tuning (eye-centered, head-centered, or intermediate). We found that tuning for optic flow was predominantly eye-centered, whereas tuning for inertial motion was intermediate but closer to head-centered. Reference frames in the two unimodal conditions were rarely matched in single neurons and uncorrelated across the population. Notably, reference frames in the combined condition varied as a function of the relative strength and spatial congruency of visual and vestibular tuning. This represents the first investigation of spatial reference frames in a naturalistic, multimodal condition in which cues may be integrated to improve perceptual performance. Our results compare favorably with the predictions of a recent neural network model that uses a recurrent architecture to perform optimal cue integration, suggesting that the brain could use a similar computational strategy to integrate sensory signals expressed in distinct frames of reference.

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Perceiving Heading in the Presence of Moving Objects

Cited by 146 publications

References 35 publications

Heading and path information from retinal flow in naturalistic environments

Heading and path information from retinal flow in naturalistic environments

A neural model of visually guided steering, obstacle avoidance, and route selection.

Spatial Reference Frames of Visual, Vestibular, and Multimodal Heading Signals in the Dorsal Subdivision of the Medial Superior Temporal Area

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