19 May 1999 Knowledge-based scene analysis with saccadic eye movements
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Abstract
The perception of an image by a human observer is usually modeled as a parallel process in which all parts of the image are treated more or less equivalently, but in reality the analysis of scenes is a highly selective procedure, in which only a small subset of image locations is processed by the precise and efficient neural machinery of foveal vision. To understand the principles behind this selection of the 'informative' regions of images we have developed a hybrid system, which consists of a combination of a knowledge-based reasoning system wit a low-level preprocessing by linear and nonlinear neural operators. This hybrid system is intended as a first step towards a compete model of the sensorimotor system of saccadic scene analysis. In the analysis of a scene, the system calculates in each step which eye movement has to be made to reach a maximum of information about the scene. The possible information gain is calculated by means of a parallel strategy which is suitable for adaptive reasoning. The output of the system is a fixation sequence, and finally, a hypothesis about the scene.
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Kerstin Schill, Kerstin Schill, Elisabeth Umkehrer, Elisabeth Umkehrer, Stephan Beinlich, Stephan Beinlich, Gerhard Krieger, Gerhard Krieger, Christoph Zetzsche, Christoph Zetzsche, } "Knowledge-based scene analysis with saccadic eye movements", Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); doi: 10.1117/12.348483; https://doi.org/10.1117/12.348483
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