Consistent Temporal Variations In Many Outdoor Scenes

2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8(2007)

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摘要
This paper details an empirical study of large image sets taken by static cameras. These images have consistent correlations over the entire image and over time scales of days to months. Simple second-order statistics of such image sets show vastly more structure than exists in generic natural images or video from moving cameras. Using a slight variant to PCA, we can decompose all cameras into comparable components and annotate images with respect to surface orientation, weather, and seasonal change. Experiments are based on a data set from 538 cameras across the United States which have collected more than 17 million images over the the last 6 months.
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关键词
principal component analysis,color,image annotation,computer science,weather forecasting,layout,statistical distributions,set theory,independent component analysis,empirical study,image resolution
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