Title :
From uncertainty to visual exploration
Author :
Whaite, P. ; Ferrie, F.P.
Author_Institution :
Comput. Vision & Robotics Lab., McGill Univ., Montreal, Que., Canada
Abstract :
The question posed is what can be inferred from ambiguity in processes of visual interpretation? Much emphasis is naturally placed on the form of constraints used to minimize ambiguity, particularly as they pertain to such issues as perceptual acceptability. The authors feel that it is perhaps more instructive to consider what can be learned from situations where different interpretations of data are possible, i.e., the ambiguity of perception. This immediately raises a number of issues regarding the characterization of ambiguity, communicating it to other visual processes, and using ambiguity to further refine visual interpretation. The context in which the authors discuss these problems is the interpretation of scene geometry in the form of volumetric models. They describe a representation for ambiguity in terms of an ellipsoid of confidence in which there is a finite probability that the true parameters of the model can be found
Keywords :
computational geometry; computer vision; computerised pattern recognition; probability; visual perception; ambiguity; ellipsoid of confidence; perceptual acceptability; scene geometry; visual exploration; visual interpretation; volumetric models; Computer vision; Ellipsoids; Intelligent robots; Laboratories; Layout; Machine intelligence; Measurement errors; Robot vision systems; Solid modeling; Uncertainty;
Conference_Titel :
Computer Vision, 1990. Proceedings, Third International Conference on
Conference_Location :
Osaka
Print_ISBN :
0-8186-2057-9
DOI :
10.1109/ICCV.1990.139620