Rule-based approach for enhancing the motion trajectories in human activity recognition

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dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorHassan S.M.
dc.contributor.authorAl-Sadek A.F.
dc.contributor.authorHemayed E.E.
dc.contributor.otherComputer Science Dept.
dc.contributor.otherOctober University for Modern Sciences and Arts
dc.contributor.otherMSA
dc.contributor.otherEgypt; Computer Engineering Dept.
dc.contributor.otherFaculty of Engineering
dc.contributor.otherCairo University
dc.contributor.otherGiza
dc.contributor.otherEgypt
dc.date.accessioned2020-01-25T19:58:32Z
dc.date.available2020-01-25T19:58:32Z
dc.date.issued2010
dc.descriptionScopus
dc.description.abstractIn this paper, we propose a rule-based system for semantically understanding and analyzing the motion of the trajectories of the human activity. The proposed system can be used as a preprocessing phase for enhancing the object detection process. Detected trajectories are classified into three categories; normal, semi-normal and abnormal trajectories according to the distances between their adjacent points. Abnormal trajectories are removed from the trajectory space. Semi-normal trajectories are broken into small normal trajectories that are linked later to form a longer normal trajectory. The proposed system does not assume a specific trajectory length and hence is more generic than similar trajectory enhancement approaches. The effectiveness of the proposed approach is demonstrated through several experimental results using known human motion datasets. � 2010 IEEE.en_US
dc.description.sponsorshipMachine Intelligence Research Labs (MIR Labs)en_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=19700187901&tip=sid&clean=0
dc.identifier.doihttps://doi.org/10.1109/ISDA.2010.5687161
dc.identifier.doiPubMed ID :
dc.identifier.isbn9.78E+12
dc.identifier.otherhttps://doi.org/10.1109/ISDA.2010.5687161
dc.identifier.otherPubMed ID :
dc.identifier.urihttps://t.ly/w1qZP
dc.language.isoEnglishen_US
dc.relation.ispartofseriesProceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10
dc.subjectAction recognitionen_US
dc.subjectHuman activity recognitionen_US
dc.subjectMotion trajectoryen_US
dc.subjectSIFT algorithmen_US
dc.subjectVisual surviellance systemen_US
dc.subjectAction recognitionen_US
dc.subjectHuman activity recognitionen_US
dc.subjectMotion trajectoriesen_US
dc.subjectSIFT algorithmen_US
dc.subjectVisual surviellance systemen_US
dc.subjectAlgorithmsen_US
dc.subjectImage recognitionen_US
dc.subjectIntelligent systemsen_US
dc.subjectSystems analysisen_US
dc.subjectTrajectoriesen_US
dc.titleRule-based approach for enhancing the motion trajectories in human activity recognitionen_US
dc.typeConference Paperen_US
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