Abstract
In our daily life experience, the angular size of an object correlates with its distance from the observer, provided that the physical size of the object remains constant. In this work, we investigated depth perception in action space (i.e., beyond the arm reach), while keeping the angular size of the target object constant. This was achieved by increasing the physical size of the target object as its distance to the observer increased. To the best of our knowledge, this is the first time that a similar protocol has been tested in action space, for distances to the observer ranging from 1.4–2.4 m. We replicated the task in virtual and real environments and we found that the performance was significantly different between the two environments. In the real environment, all participants perceived the depth of the target object precisely. Whereas, in virtual reality (VR) the responses were significantly less precise, although, still above chance level in 16 of the 20 observers. The difference in the discriminability of the stimuli was likely due to different contributions of the convergence and the accommodation cues in the two environments. The values of Weber fractions estimated in our study were compared to those reported in previous studies in peripersonal and action space.
Highlights
Various visual cues contribute to the perception of depth in humans (Bruno and Cutting, 1988; Nagata, 1991; Landy et al, 1995; Ware, 2004)
Virtual Reality The Akaike information criterion (AIC) was smaller in modelVR2 (AIC2 = 1335.1) than in modelVR1 (AIC1 = 3003.9) revealing large differences between the observers in the discriminability of the stimuli (Figure 3)
The Likelihood Ratio test (LR test) confirmed that modelVR2 provided a better fit to the data than modelVR1 and modelVR3 (p < 0.001)
Summary
Various visual cues contribute to the perception of depth in humans (Bruno and Cutting, 1988; Nagata, 1991; Landy et al, 1995; Ware, 2004). According to several studies (Bruno and Cutting, 1988; Landy et al, 1995), the combined depth estimate is based on a weighted average of these multiple cues. The relative weight of the different cues (and their contribution to the combined depth estimate) changes depending on the target distance from the observer (Cutting and Vishton, 1995).
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