Mouse Behavior Recognition with The Wisdom of Crowd
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MIT-CSAIL-TR-2013-023.pdf
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Author(s)
Ni, Yuzhao
Frogner, Charles A.
Poggio, Tomaso A
Advisor(s)
Tomaso Poggio
Date Issued
September 19, 2013
Series/Report no.
MIT-CSAIL-TR-2013-023
CBCL-314
Abstract
In this thesis, we designed and implemented a crowdsourcing system to annotatemouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional labeling tools in crowdsourcing platform, as well as the design of probabilistic inference algorithms that predict the true labels and the workers' expertise from multiple workers' responses. Our algorithms are shown to perform better than majority vote heuristic. We also carried out extensive experiments to determine the effectiveness of our labeling tool, inference algorithms and the overall system.
Subjects
crowdsourcing
video labeling
human computation
mouse phenotyping
action recognition
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