9 January 1984 A Model Driven System for Contextual Scene Analysis
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Existing strategies for the identification of objects in a scene are based upon classical pattern recognition approaches. The basic concept involved centers around the extraction of a set of statistical features for each object detected in a scene, followed by the application of a classifier which attempts to derive the decision boundaries that separate these objects into classes. As statistical features are quite sensitive to noise, this approach has led to problems due to the inability of classifiers to identify accurate feature set separation in less than ideal conditions. A global approach utilizing the contextual information in a scene currently discarded offers the most promise in overcoming the short-comings of current object classification methods.
© (1984) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John F. Gilmore and Andrew J. Spiessbach "A Model Driven System for Contextual Scene Analysis", Proc. SPIE 0432, Applications of Digital Image Processing VI, (9 January 1984); doi: 10.1117/12.936676; https://doi.org/10.1117/12.936676


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