Minimal theory of 3D vision: new approach to visual scale and visual shape

Linear perspective cues have a greater effect on the perceptual rescaling of distant stimuli than textures in the virtual environment

The presence of pictorial depth cues in virtual environments is important for minimising distortions driven by unnatural viewing conditions (e.g., vergence-accommodation conflict). Our aim was to determine how different pictorial depth cues affect size constancy in virtual environments under binocular and monocular viewing conditions. We systematically removed linear perspective cues and textures of a hallway in a virtual environment. The experiment was performed using the method of constant stimuli. The task required participants to compare the size of 'far' (10 m) and 'near' (5 m) circles displayed inside a virtual environment with one or both or none of the pictorial depth cues. Participants performed the experiment under binocular and monocular viewing conditions while wearing a virtual reality headset. ANOVA revealed that size constancy was greater for both the far and the near circles in the virtual environment with pictorial depth cues compared to the one without cues. However, the effect of linear perspective cues was stronger than textures, especially for the far circle. We found no difference between the binocular and monocular viewing conditions across the different virtual environments. We conclude that linear perspective cues exert a stronger effect than textures on the perceptual rescaling of far stimuli placed in the virtual environment, and that this effect does not vary between binocular and monocular viewing conditions.

New Approaches to 3D Vision

New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D vision in computer vision (SLAM: simultaneous localization and mapping), animal navigation (cognitive maps), and human vision (optimal cue integration) start from the assumption that the aim of 3D vision is to provide an accurate 3D model of the world, the new approaches to 3D vision explored in this issue challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models or no model at all. This issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. This article is part of a discussion meeting issue 'New approaches to 3D vision'.