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David pioneered the use of three-dimensional geometric models for tracking flexible structures (e.g. the human body) in natural scenes, and contributed to establishing statistical approaches to learning of shape and motion as one of the pre-eminent paradigms in the field. Current research is on representation and learning of activities from video, specifically models of interaction, and applications of machine learning in science and engineering. Part of this work is exploring the integration of vision within a broader cognitive framework that includes audition, language, action, and reasoning.
David pioneered the use of three-dimensional geometric models for tracking flexible structures (e.g. the human body) in natural scenes, and contributed to establishing statistical approaches to learning of shape and motion as one of the pre-eminent paradigms in the field. Current research is on representation and learning of activities from video, specifically models of interaction, and applications of machine learning in science and engineering. Part of this work is exploring the integration of vision within a broader cognitive framework that includes audition, language, action, and reasoning.
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crossref(2023)
2023 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS, ICCVW (2023): 1041-1048
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