Title :
Towards a computational theory of model based vision and perception
Author_Institution :
David Sarnoff Res. Center, Princeton, NJ, USA
Abstract :
When given partial data, a model based approach requires that pictures consistent with the model are chosen as plausible interpretations of the data. The author presents a computational theory that relates degrees of freedom in such models to the number of pixels that carry useful information. It is shown that in models with a finite number of degrees of freedom it is always possible to find a consistent interpretation from a finite number of pixels
Keywords :
computer vision; computerised pattern recognition; computerised picture processing; computational theory; degrees of freedom; model based vision; partial data; perception; pictures; pixels; plausible interpretations; Cleaning; Computational modeling; Computer vision; Filtering; Layout; Noise level; Psychology; Visual perception;
Conference_Titel :
Computer Vision, 1990. Proceedings, Third International Conference on
Conference_Location :
Osaka
Print_ISBN :
0-8186-2057-9
DOI :
10.1109/ICCV.1990.139531
