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4 May 2006Processing of visual information in the visual and object buffers of scene understanding based on network-symbolic models
Modern computer vision systems suffer from the lack of human-like abilities to understand a visual scene, detect,
unambiguously identify and recognize objects. Bottom-up fine-scale segmentation of image with grouping into regions
can rarely be effective for real world images if applied to the whole image without having clear criteria of how further to
combine obtained small distinctive neighbor regions into meaningful objects. On a certain scale, an object or a pattern
can be perceived just as an object or a pattern rather than a set of neighboring regions. Therefore, a region of interest,
where the object or pattern can be located, must be established first. Rough but wide peripheral human vision serves to
this goal, while narrow but precise foveal vision analyzes and recognizes the object from the center of the region of
interest after separating it from its background. Unlike the traditional computer vision models, biologically-inspired
Network-Symbolic models convert image information into an 'understandable' Network-Symbolic format, which is
similar to relational knowledge models. The equivalent of interaction between peripheral and foveal systems in the
network-symbolic system is achieved via interaction of the Visual and Object Buffers and the top-level knowledge
system. This article describes the principles of data representation and processing of information in Visual and Object
buffers that allow for scene analysis and understanding with identification and recognition of objects in the visual scene.
Gary Kuvich
"Processing of visual information in the visual and object buffers of scene understanding based on network-symbolic models", Proc. SPIE 6246, Visual Information Processing XV, 624603 (4 May 2006); https://doi.org/10.1117/12.662168
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Gary Kuvich, "Processing of visual information in the visual and object buffers of scene understanding based on network-symbolic models," Proc. SPIE 6246, Visual Information Processing XV, 624603 (4 May 2006); https://doi.org/10.1117/12.662168