Automatic Retrieval of Videos of Stereotyped and Repetitive Movements
Collecting large corpora of video data has become common practice among researchers and clinicians studying autism (e.g., Watt et.al., 2008). One of the difficulties in analyzing video data stems from the need for human coders to browse all of the content in order to manually annotate the occurrence of specific behaviors of interest, a time intensive and laborious process. We demonstrate a collaboration between computer vision research and developmental psychology aimed at developing automated tools to speed up the annotation process. The specific context of this work is to assist in the automatic retrieval of gross motor physical stereotypies from video based on a single example identified in the video by a human coder.
Arridhana Ciptadi, Matthew S. Goodwin, and James M. Rehg. Movement Pattern Histogram for Action Recognition and Retrieval. In Proc. IEEE European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, September, 2014.
To be released
Portions of this work were supported in part by NSF Expedition Award number 0960618 and 1029679.
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