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Sergei Gepshtein; Solid field of visibility. Journal of Vision 2016;16(12):1002. doi: https://doi.org/10.1167/16.12.1002.
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© ARVO (1962-2015); The Authors (2016-present)
Previous attempts to characterize the structure of visual space concentrated on perceived relationships between "objects, backgrounds, and the self" (Indow, 1991), including metric and topological measures of such relationships. I consider a different approach which is simpler and more basic in that it concerns visibility of object and patterns. Indeed, one's experience of the relationship between visual objects and patterns is predicated on the ability to see them. I start by developing a model of the structure of solid space by tracing visibility of patterns as a function of viewing distance. For example, a luminance grating projected on an opaque screen will create a retinal image of increasing spatial frequency as the viewing distance increases. The contrast sensitivity function predicts the distances at which the grating will be visible or not. The boundaries of visibility depend on whether the grating is moving. This approach allows one to predict visibility for every location in the space that contains any three-dimensional arrangement of static and dynamic patterns. Since the predicted visibility has a value for every location and it varies smoothly across locations, I describe the predictions in terms of a "solid field of visibility." The field is made up of solid regions which contain different visual information and which may overlap or nest in one another. The predictions were tested using static and dynamic patterns projected on large screens propelled through space by large-scale robotics at the IDEAS Robotics Laboratory (UCLA Department of Architecture and Urban Design) in collaboration with the architect Greg Lynn (UCLA) and the designer Alex McDowell (USC). The results confirmed predictions of the model in several respects, including spatial locations of the boundaries between solid regions of visibility and the notion that the boundaries are displaced by adding dynamic content to the patterns.
Meeting abstract presented at VSS 2016
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