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dc.contributor.authorŞaykol, E.en_US
dc.contributor.authorBaştan M.en_US
dc.contributor.authorGüdükbay U.en_US
dc.contributor.authorUlusoy, Ö.en_US
dc.date.accessioned2016-02-08T09:56:08Z
dc.date.available2016-02-08T09:56:08Z
dc.date.issued2010en_US
dc.identifier.issn0091-3286
dc.identifier.urihttp://hdl.handle.net/11693/22144
dc.description.abstractThe huge amount of video data generated by surveillance systems necessitates the use of automatic tools for their efficient analysis, indexing, and retrieval. Automated access to the semantic content of surveillance videos to detect anomalous events is among the basic tasks; however, due to the high variability of the audio-visual features and large size of the video input, it still remains a challenging task, though a considerable amount of research dealing with automated access to video surveillance has appeared in the literature. We propose a keyframe labeling technique, especially for indoor environments, which assigns labels to keyframes extracted by a keyframe detection algorithm, and hence transforms the input video to an event-sequence representation. This representation is used to detect unusual behaviors, such as crossover, deposit, and pickup, with the help of three separate mechanisms based on finite state automata. The keyframes are detected based on a grid-based motion representation of the moving regions, called the motion appearance mask. It has been shown through performance experiments that the keyframe labeling algorithm significantly reduces the storage requirements and yields reasonable event detection and classification performance. © 2010 Society of Photo-Optical Instrumentation Engineers.en_US
dc.language.isoEnglishen_US
dc.source.titleOptical Engineeringen_US
dc.relation.isversionofhttp://dx.doi.org/10.1117/1.3509270en_US
dc.subjectAfter-the-fact analysisen_US
dc.subjectAnomaly detectionen_US
dc.subjectFinite state automataen_US
dc.subjectKeyframe detectionen_US
dc.subjectScenario-based querying and retrievalen_US
dc.subjectVideo surveillanceen_US
dc.subjectAfter-the-facten_US
dc.subjectAlgorithmsen_US
dc.subjectFinite automataen_US
dc.subjectMonitoringen_US
dc.subjectSearch enginesen_US
dc.subjectSemanticsen_US
dc.subjectSecurity systemsen_US
dc.titleKeyframe labeling technique for surveillance event classificationen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage[1]en_US
dc.citation.epage[12]en_US
dc.citation.volumeNumber49en_US
dc.citation.issueNumber11en_US
dc.identifier.doi10.1117/1.3509270en_US
dc.publisherS P I E - International Society for Optical Engineeringen_US


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