Reliability and relative weighting of visual and nonvisual information for perceiving direction of self-motion during walking
Author(s) -
J. A. Saunders
Publication year - 2014
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/14.3.24
Subject(s) - heading (navigation) , weighting , sensory cue , parallax , artificial intelligence , computer vision , computer science , optical flow , sensory system , reliability (semiconductor) , motion (physics) , psychology , geodesy , cognitive psychology , geography , physics , acoustics , image (mathematics) , power (physics) , quantum mechanics
Direction of self-motion during walking is indicated by multiple cues, including optic flow, nonvisual sensory cues, and motor prediction. I measured the reliability of perceived heading from visual and nonvisual cues during walking, and whether cues are weighted in an optimal manner. I used a heading alignment task to measure perceived heading during walking. Observers walked toward a target in a virtual environment with and without global optic flow. The target was simulated to be infinitely far away, so that it did not provide direct feedback about direction of self-motion. Variability in heading direction was low even without optic flow, with average RMS error of 2.4°. Global optic flow reduced variability to 1.9°–2.1°, depending on the structure of the environment. The small amount of variance reduction was consistent with optimal use of visual information. The relative contribution of visual and nonvisual information was also measured using cue conflict conditions. Optic flow specified a conflicting heading direction (±5°), and bias in walking direction was used to infer relative weighting. Visual feedback influenced heading direction by 16%–34% depending on scene structure, with more effect with dense motion parallax. The weighting of visual feedback was close to the predictions of an optimal integration model given the observed variability measures.link_to_OA_fulltex
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