Ch.8: Brown, Coombs, & Soong, 1992 Coombs & Brown, 1992 Coombs & Brown, 1993 Krotkov & Bajcsy, 1993 see also Schechner & Kiryati, 2000 for an influential discussion of distance triangulation in computer vision).ģ. Indeed, vergence played a central role in the ‘active vision’ revolution in computer vision in the late 1980s and early 1990s (see Krotkov & Kories, 1988 Krotkov, Fuma, & Summers, 1988 Abbott & Ahuja, 1988 Geiger & Yuille, 1989 Krotkov, 1989 Krotkov, Henriksen, & Kories, 1990 Abbott & Ahuja, 1990 Olson & Coombs, 1991 Blake & Yuille, 1992, esp. Computer Vision: If you were to reverse-engineer distance estimates for a visual system based on two rotating cameras (or eyes), vergence would seem like the natural solution. See Bishop and Pettigrew ( 1986) for an optimistic account of 3D vision without the need to infer 3D content from the 2D retinal images, and Clark and Yuille ( 1990), Ch.1 for a skeptical one.Ģ. Theoretically, this is true of other cues to absolute distance as well (such as accommodation and motion parallax) which is why “conventional wisdom” has traditionally identified “eye vergence, accommodation (focusing the image), binocular disparity, and motion parallax” as the four “primary cues” to depth (Rogers, 2017). Instead, the visual system is able to triangulate distance from the rotation of the eyes (Parker, Smith, & Krug, 2016 Banks, Hoffman, Kim, & Wetzstein, 2016 Wolfe et al., 2019).
There is no need to infer 3D content from the 2D retinal images. Triangulation: Extracting absolute distance from vergence relies on simple principles of geometry. Since Kepler ( 1604) and Descartes ( 1637), this mechanism, known as ‘vergence’, has been thought of as one of the visual system’s most important absolute distance cues. The closer an object is, the more the two eyes have to rotate to fixate upon it.
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