Paper
23 June 2003 MPEG-7 and image understanding systems
Author Affiliations +
Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.502771
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland
Abstract
Inexpensive computer hardware and optical devices has made image/video applications available even for private individuals. This has created a huge demand for image and multimedia databases and other systems, which work with visual information. Analysis of visual information has not been completely formalized and automated yet. The reason for that is a long tradition of separation of vision and knowledge subsystems. However, brain researches show that vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty in real images via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. It is hard to split such system apart. Brain does not recreate 3-D image of visual scene, but analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Vision mechanisms can never be completely understood separately from the informational processes related to knowledge and intelligence. MPEG-7 is an industry-wide effort to incorporate knowledge into image/video code. This article describes basic principles of integration low-level image processing with high-level knowledge reasoning, and shows how Image Understanding systems can utilize MPEG-7 standard. Such applications can add to the standard the power of image understanding.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gary Kuvich "MPEG-7 and image understanding systems", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.502771
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KEYWORDS
Visualization

Information visualization

Image understanding

Systems modeling

Brain

Image processing

Visual process modeling

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