Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2013:
Metadata Last Update2020: administrator
Citation KeyAlmeidaJung:2013:ChDeHu
TitleChange detection in human crowds
Access Date2021, Jan. 27
Number of Files1
Size10550 KiB
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Author1 Almeida, Igor Rodrigues de
2 Jung, Claudio Rosito
Affiliation1 Federal University of Rio Grande do Sul
2 Federal University of Rio Grande do Sul
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
DateAug. 5-8, 2013
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2013-07-05 19:01:14 :: -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsCrowd analysis, Unusual event detection, Video surveillance.
AbstractThis paper presents a method to detect unusual behavior in human crowds based on histograms of velocities in world coordinates. A combination of background removal and optical flow is used to extract the global motion at each image frame, discarding small motion vectors due artifacts such as noise, non-stationary background pixels and compression issues. Using a calibrated camera, the global motion can be estimated, and it is used to build a 2D histogram containing information of speed and direction for all frames. Each frame is compared with a set of previous frames by using a histogram comparison metric, resulting in a similarity vector. This vector is then used to determine changes in the crowd behavior, also allowing a classification based on the nature of the change in time: short or long-term changes. The method was tested on publicly available datasets involving crowded scenarios.
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