The Detection Of Nonplanar Surfaces In Visual Space
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The Detection of Nonplanar Surfaces in Visual Space
First published in 1984. This monograph is the third in a series that examines the nature of a midlevel visual process relatively uncontaminated by either peripheral receptor or central cognitive processing. The paradigm utilized in this study selectively assays what seems to be a relatively fixed algorithmic mechanism involved in the extraction of dotted stimulus-forms from masks consisting of random dots.
The Detection of Nonplanar Surfaces in Visual Space
This monograph presents the results of a series of 17 experiments designed to provide a partial answer to two questions concerning the detection of dotted forms in dotted visual masks: (1) What is the effect of the spatial geometry of three-dimensional, nonplanar forms on their detectability? (2) What is the effect on the signal-to-noise ratio on their detectability? The results of the study indicate that the spatial geometry exerts virtually no effect until a threshold level of geometrical complexity is exceeded by the stimulus forms. Beyond that threshold, the effects of form are significant but modest in absolute amplitude. The results further indicate that a putative large effect of form obtained with sinusoidal stimuli actually results form a violation of the Shannon-Weaver sampling theorem from information theory and is thus due to inadequate definition of the form rather than to the nature of the form. On the other hand, the signal-to-noise ration strongly influences detectability, regardless of whether it is manipulated by varying the number of dots in the stimulus-form or by varying the number of masking dots. This study failed to extend a highly successful autocorrelation-type theory from twp-dimensions to three-dimensions. The implications and background of this study are discussed in detail.
The Swimmer
This research monograph describes a large programming project in which an underwater organism, capable of perceiving, learning, deciding, and navigating, is computationally simulated. The developed computational model serves as a contemporary theory of perceptual-motor performance, embodying much of what is known about human vision and some of what is known about other cognitive processes. This artificial intelligence project has substantial contributions to make to the development of autonomous underwater vehicles. It also makes a specific theoretical statement about the organization and nature of organic perceptual motor systems that may be useful to psychologists, neuroscientists, and theoreticians in a number of other fields.