17 May 2011 Cognitive modeling to predict video interpretability
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Abstract
Processing framework for cognitive modeling to predict video interpretability is discussed. Architecture consists of spatiotemporal video preprocessing, metric computation, metric normalization, pooling of like metric groups with masking adjustments, multinomial logistic pooling of Minkowski pooled groups of similar quality metrics, and estimation of confidence interval of final result.
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Darrell L. Young, Tariq Bakir, "Cognitive modeling to predict video interpretability", Proc. SPIE 8053, Geospatial InfoFusion Systems and Solutions for Defense and Security Applications, 80530M (17 May 2011); doi: 10.1117/12.887100; https://doi.org/10.1117/12.887100
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KEYWORDS
Video

Video surveillance

Cognitive modeling

Signal to noise ratio

Video compression

Cameras

Quality measurement

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