An area-based decision rule for people-counting systems

Hyun Hee Park, Hyung Gu Lee, Seung In Noh, Jaihie Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In this paper, we propose an area-based decision rule for counting the number of people that pass through a given ROI (Region of Interest). This decision rule divides obtained images into 72 sectors and the size of the person is trained to calculate the mean and variance values for each divided sector. These values are then stored in table form and can be used to count people in the future. We also analyze various movements that people perform in the real world. For instance, during busy hours, people frequently merge and split with each other. Therefore, we propose a system for counting the number of passing people more accurately and a way of discovering the direction of their paths.

Original languageEnglish
Title of host publicationMultimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings
PublisherSpringer Verlag
Pages450-457
Number of pages8
ISBN (Print)3540393927, 9783540393924
Publication statusPublished - 2006 Jan 1
EventInternational Workshop on Multimedia Content Representation, Classification and Security, MRCS 2006 - Istanbul, Turkey
Duration: 2006 Sep 112006 Sep 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4105 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Workshop on Multimedia Content Representation, Classification and Security, MRCS 2006
CountryTurkey
CityIstanbul
Period06/9/1106/9/13

Fingerprint

Decision Rules
Counting
Sector
Region of Interest
Divides
Table
Person
Count
Calculate
Path
Movement
Form

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Park, H. H., Lee, H. G., Noh, S. I., & Kim, J. (2006). An area-based decision rule for people-counting systems. In Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings (pp. 450-457). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4105 LNCS). Springer Verlag.
Park, Hyun Hee ; Lee, Hyung Gu ; Noh, Seung In ; Kim, Jaihie. / An area-based decision rule for people-counting systems. Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings. Springer Verlag, 2006. pp. 450-457 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Park, HH, Lee, HG, Noh, SI & Kim, J 2006, An area-based decision rule for people-counting systems. in Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4105 LNCS, Springer Verlag, pp. 450-457, International Workshop on Multimedia Content Representation, Classification and Security, MRCS 2006, Istanbul, Turkey, 06/9/11.

An area-based decision rule for people-counting systems. / Park, Hyun Hee; Lee, Hyung Gu; Noh, Seung In; Kim, Jaihie.

Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings. Springer Verlag, 2006. p. 450-457 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4105 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Park HH, Lee HG, Noh SI, Kim J. An area-based decision rule for people-counting systems. In Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings. Springer Verlag. 2006. p. 450-457. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).