Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/583527
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dc.contributor.authorZheng Maen_US
dc.contributor.authorAntoni B. Chanen_US
dc.date.accessioned2020-05-20T08:31:37Z-
dc.date.available2020-05-20T08:31:37Z-
dc.date.issued2016en_US
dc.identifier.issn1051-8215en_US
dc.identifier.issn1558-2205en_US
dc.identifier.other10.1109/TCSVT.2015.2489418en_US
dc.identifier.urihttp://localhost/handle/Hannan/165220en_US
dc.identifier.urihttp://localhost/handle/Hannan/583527-
dc.description.abstractWe propose an integer programming method for estimating the instantaneous count of pedestrians crossing a line of interest (LOI) in a video sequence. Through a line sampling process, the video is first converted into a temporal slice image. Next, the number of people is estimated in a set of overlapping sliding windows on the temporal slice image, using a regression function that maps from local features to a count. Given that the count in a sliding window is the sum of the instantaneous counts in the corresponding time interval, an integer programming method is proposed to recover the number of pedestrians crossing the LOI in each frame. Integrating over a specific time interval yields the cumulative count of pedestrians crossing the line. Compared with current methods for line counting, our proposed approach achieves state-of-the-art performance on several challenging crowd video data sets.en_US
dc.publisherIEEEen_US
dc.relation.haspart7295569.pdfen_US
dc.subjectlocal feature|Crowd counting|integer programmingen_US
dc.titleCounting People Crossing a Line Using Integer Programming and Local Featuresen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
dc.journal.titleIEEE Transactions on Circuits and Systems for Video Technologyen_US
Appears in Collections:2016

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorZheng Maen_US
dc.contributor.authorAntoni B. Chanen_US
dc.date.accessioned2020-05-20T08:31:37Z-
dc.date.available2020-05-20T08:31:37Z-
dc.date.issued2016en_US
dc.identifier.issn1051-8215en_US
dc.identifier.issn1558-2205en_US
dc.identifier.other10.1109/TCSVT.2015.2489418en_US
dc.identifier.urihttp://localhost/handle/Hannan/165220en_US
dc.identifier.urihttp://localhost/handle/Hannan/583527-
dc.description.abstractWe propose an integer programming method for estimating the instantaneous count of pedestrians crossing a line of interest (LOI) in a video sequence. Through a line sampling process, the video is first converted into a temporal slice image. Next, the number of people is estimated in a set of overlapping sliding windows on the temporal slice image, using a regression function that maps from local features to a count. Given that the count in a sliding window is the sum of the instantaneous counts in the corresponding time interval, an integer programming method is proposed to recover the number of pedestrians crossing the LOI in each frame. Integrating over a specific time interval yields the cumulative count of pedestrians crossing the line. Compared with current methods for line counting, our proposed approach achieves state-of-the-art performance on several challenging crowd video data sets.en_US
dc.publisherIEEEen_US
dc.relation.haspart7295569.pdfen_US
dc.subjectlocal feature|Crowd counting|integer programmingen_US
dc.titleCounting People Crossing a Line Using Integer Programming and Local Featuresen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
dc.journal.titleIEEE Transactions on Circuits and Systems for Video Technologyen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7295569.pdf7.27 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZheng Maen_US
dc.contributor.authorAntoni B. Chanen_US
dc.date.accessioned2020-05-20T08:31:37Z-
dc.date.available2020-05-20T08:31:37Z-
dc.date.issued2016en_US
dc.identifier.issn1051-8215en_US
dc.identifier.issn1558-2205en_US
dc.identifier.other10.1109/TCSVT.2015.2489418en_US
dc.identifier.urihttp://localhost/handle/Hannan/165220en_US
dc.identifier.urihttp://localhost/handle/Hannan/583527-
dc.description.abstractWe propose an integer programming method for estimating the instantaneous count of pedestrians crossing a line of interest (LOI) in a video sequence. Through a line sampling process, the video is first converted into a temporal slice image. Next, the number of people is estimated in a set of overlapping sliding windows on the temporal slice image, using a regression function that maps from local features to a count. Given that the count in a sliding window is the sum of the instantaneous counts in the corresponding time interval, an integer programming method is proposed to recover the number of pedestrians crossing the LOI in each frame. Integrating over a specific time interval yields the cumulative count of pedestrians crossing the line. Compared with current methods for line counting, our proposed approach achieves state-of-the-art performance on several challenging crowd video data sets.en_US
dc.publisherIEEEen_US
dc.relation.haspart7295569.pdfen_US
dc.subjectlocal feature|Crowd counting|integer programmingen_US
dc.titleCounting People Crossing a Line Using Integer Programming and Local Featuresen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
dc.journal.titleIEEE Transactions on Circuits and Systems for Video Technologyen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7295569.pdf7.27 MBAdobe PDFThumbnail
Preview File