Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/583527
Title: Counting People Crossing a Line Using Integer Programming and Local Features
Authors: Zheng Ma;Antoni B. Chan
subject: local feature|Crowd counting|integer programming
Year: 2016
Publisher: IEEE
Abstract: We 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.
URI: http://localhost/handle/Hannan/165220
http://localhost/handle/Hannan/583527
ISSN: 1051-8215
1558-2205
volume: 26
issue: 10
Appears in Collections:2016

Files in This Item:
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7295569.pdf7.27 MBAdobe PDFThumbnail
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Title: Counting People Crossing a Line Using Integer Programming and Local Features
Authors: Zheng Ma;Antoni B. Chan
subject: local feature|Crowd counting|integer programming
Year: 2016
Publisher: IEEE
Abstract: We 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.
URI: http://localhost/handle/Hannan/165220
http://localhost/handle/Hannan/583527
ISSN: 1051-8215
1558-2205
volume: 26
issue: 10
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7295569.pdf7.27 MBAdobe PDFThumbnail
Preview File
Title: Counting People Crossing a Line Using Integer Programming and Local Features
Authors: Zheng Ma;Antoni B. Chan
subject: local feature|Crowd counting|integer programming
Year: 2016
Publisher: IEEE
Abstract: We 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.
URI: http://localhost/handle/Hannan/165220
http://localhost/handle/Hannan/583527
ISSN: 1051-8215
1558-2205
volume: 26
issue: 10
Appears in Collections:2016

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