Direct Vehicle Collision Detection from Motion in Driving Video

dc.contributor.authorKilicarslan, Mehmet
dc.contributor.authorZheng, Jiang Yu
dc.contributor.departmentComputer and Information Science, School of Scienceen_US
dc.date.accessioned2018-03-28T17:12:16Z
dc.date.available2018-03-28T17:12:16Z
dc.date.issued2017-06
dc.description.abstractThe objective of this work is the instantaneous computation of Time-to-Collision (TTC) for potential collision only from motion information captured with a vehicle borne camera. The contribution is the detection of dangerous events and degree directly from motion divergence in the driving video, which is also a clue used by human drivers, without applying vehicle recognition and depth measuring in prior. Both horizontal and vertical motion divergence are analyzed simultaneously in several collision sensitive zones. Stable motion traces of linear feature components are obtained through filtering in the motion profiles. As a result, this avoids object recognition, and sophisticated depth sensing. The fine velocity computation yields reasonable TTC accuracy so that the video camera can achieve collision avoidance alone from size changes of visual patterns.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationKilicarslan, M., & Zheng, J. Y. (2017). Direct vehicle collision detection from motion in driving video. In 2017 IEEE Intelligent Vehicles Symposium (IV) (pp. 1558–1564). https://doi.org/10.1109/IVS.2017.7995931en_US
dc.identifier.urihttps://hdl.handle.net/1805/15729
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/IVS.2017.7995931en_US
dc.relation.journal2017 IEEE Intelligent Vehicles Symposiumen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectaccident preventionen_US
dc.subjectdriver information systemsen_US
dc.subjectimage motion analysisen_US
dc.titleDirect Vehicle Collision Detection from Motion in Driving Videoen_US
dc.typeArticleen_US
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