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Long-Term Human Participation Detection Using A Dynamic Scene Analysis Model, Wenjing Shi
Long-Term Human Participation Detection Using A Dynamic Scene Analysis Model, Wenjing Shi
Electrical and Computer Engineering ETDs
The dissertation develops new methods for assessing student participation in long (>1 hour) classroom videos. First, the dissertation introduces the use of multiple image representations based on raw RGB images and AM-FM components to detect specific student groups. Second, a dynamic scene analysis model is developed for tracking under occlusion and variable camera angles. Third, a motion vector projection system identifies instances of students talking.
The proposed methods are validated using digital videos from the Advancing Out-of-school Learning in Mathematics and Engineering (AOLME) project. The proposed methods are shown to provide better group detection, and better talking detection at …