Title :
Quasi-periodic event analysis for social game retrieval
Author :
Wang, Ping ; Abowd, Gregory D. ; Rehg, James M.
Author_Institution :
Health Systems Institute and GVU Center, School of Interactive Computing, Georgia Institute of Technology, USA
fDate :
Sept. 29 2009-Oct. 2 2009
Abstract :
A new problem of retrieving social games from unstructured videos is proposed. Social games are characterized by repetitions (with variations) of alternating turns between two players. We define games as quasi-periodic motion patterns in video based on their repetitiveness property. We have developed an algorithm to extract such patterns from video. The patterns extracted by our method, from video clips of social games taken from YouTube, are shown to correspond to meaningful stages of the games. We demonstrate promising results in retrieving social games from unstructured, lab-recorded footage of children´s play, and identifying social interactions in a dataset of approximately 3.75 hours of home movies.
Keywords :
Cameras; Computer vision; Data mining; Games; Information retrieval; Motion analysis; Motion estimation; Motion pictures; Pediatrics; Videos;
Conference_Titel :
Computer Vision, 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-4420-5
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2009.5459151