Cue combination for 3D location judgements
Author(s) -
Ellen Svarverud,
Stuart J. Gilson,
Andrew Glennerster
Publication year - 2010
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/10.1.5
Subject(s) - parallax , artificial intelligence , computer vision , computer science , object (grammar) , matching (statistics) , depth perception , perception , task (project management) , texture (cosmology) , position (finance) , scale (ratio) , virtual reality , binocular disparity , pattern recognition (psychology) , stereopsis , mathematics , psychology , statistics , image (mathematics) , geography , management , cartography , finance , neuroscience , economics
Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only 'physical' (stereo and motion parallax) or 'texture-based' cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the target relative to other objects was varied, the ratio of 'physical' to 'texture-based' thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying traditional models of 3D reconstruction.
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