2011
DOI: 10.1167/10.1.5
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Cue combination for 3D location judgements

Abstract: 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 'phy… Show more

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Cited by 38 publications
(48 citation statements)
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“…Subjectively, the transition was seamless. In none of the trials, neither those on which the room expanded nor those on which it remained static did participants notice any change in the size of the room [15], [17]. This is consistent with previous findings using large-scale stimuli in which looming cues are eliminated [19], [20].…”
Section: Resultssupporting
confidence: 91%
See 1 more Smart Citation
“…Subjectively, the transition was seamless. In none of the trials, neither those on which the room expanded nor those on which it remained static did participants notice any change in the size of the room [15], [17]. This is consistent with previous findings using large-scale stimuli in which looming cues are eliminated [19], [20].…”
Section: Resultssupporting
confidence: 91%
“…In fact, using the best fitting estimates from Svarverud et al [17] which estimate the weight applied to ‘texture-based’ and ‘physical’ cues across different conditions, we can also predict the magnitude of the effect we would expect to see in the current experiment. The mean ratio of vergence angles to square D via C or via B is 0.77 (s.d.…”
Section: Resultsmentioning
confidence: 80%
“…are separately weighted according to their reliability (Landy, Maloney, Johnston, & Young, 1995), and then combined optimally. Many studies have shown that human observers combine cues in a way that is consistent with this optimal model (Ernst & Banks, 2002; Hillis, Watt, Landy, & Banks, 2004; Knill & Saunders, 2003; Svarverud, Gilson, & Glennerster, 2010). …”
Section: Introductionmentioning
confidence: 84%
“…There are previous extensive researches on depth perception of 3D models using immersive or volumetric 3D environments [3], [4], [5], [6], [8], [9], but the novelty of this experimental study is the comparison of the depth perception of CAD models using two distinct display modalities: monoscopic desktop system and 3D stereoscopic immersive environment.…”
Section: Introductionmentioning
confidence: 99%