Object Recognition in Videos Utilizing Hierarchical and Temporal Objectness with Deep Neural Networks
This dissertation develops a novel system for object recognition in videos. The input of the system is a set of unconstrained videos containing a known set of objects. The output is the locations and categories for each object in each frame across all videos. Initially, a shot boundary detection alg...
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| Format: | Others |
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DigitalCommons@USU
2017
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| Online Access: | https://digitalcommons.usu.edu/etd/6531 https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=7703&context=etd |