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Conference papers
Towards Unsupervised Sudden Group Movement Discovery for Video Surveillance
Abstract : This paper presents a novel and unsupervised approach for discovering "sudden" movements in video surveillance videos. The proposed approach automatically detects quick motions in a video, corresponding to any action. A set of possible actions is not required and the proposed method successfully detects potentially alarm-raising actions without training or camera calibration. Moreover, the system uses a group detection and event recognition framework to relate detected sudden movements and groups of people, and provide a semantical interpretation of the scene. We have tested our approach on a dataset of nearly 8 hours of videos recorded from two cameras in the Parisian subway for a European Project. For evaluation, we annotated 1 hour of sequences containing 50 sudden movements.
Cited literature [18 references]
https://hal.inria.fr/hal-00878580
Contributor : Sofia Zaidenberg <>
Submitted on : Wednesday, October 30, 2013 - 12:23:28 PM
Last modification on : Thursday, March 5, 2020 - 5:34:24 PM
Long-term archiving on: : Friday, January 31, 2014 - 9:25:27 AM
Contributor : Sofia Zaidenberg <>
Submitted on : Wednesday, October 30, 2013 - 12:23:28 PM
Last modification on : Thursday, March 5, 2020 - 5:34:24 PM
Long-term archiving on: : Friday, January 31, 2014 - 9:25:27 AM
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ZaidenbergVISAPP2014.pdf
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