What Does Learning About Time Tell About Outdoor Scenes?

Zeyu Zhang, Callista Baker, Noor Azam-Naseeruddin, Jingzhou Shen,Robert Pless

2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)(2022)

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摘要
In this paper, we explore the potential of utilizing time-stamps as labels for Deep Learning from webcams, surveillance cameras, and other fixed viewpoint image situations. Specifically, we explore if learning to classify images by the time they were taken uncovers interesting patterns and behaviors in the scenes captured by these cameras. We describe approaches to building datasets with large quantities of images and their accompanying labels, making them suitable for large-scale deep learning approaches. We share our results from the initial deep learning experiments.
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