A Robust System for Counting People Using an Infrared Sensor and a Camera

dc.authoridErden, Fatih/0000-0002-1708-3063
dc.authoridAlkar, Ali Ziya/0000-0002-5880-2423
dc.authorscopusid57189290485
dc.authorscopusid6506200184
dc.authorscopusid57197548971
dc.authorwosidALKAR, ALI ZİYA/G-5897-2013
dc.authorwosidErden, Fatih/B-3968-2015
dc.contributor.authorErden, Fatih
dc.contributor.authorAlkar, Ali Ziya
dc.contributor.authorCetin, Ahmet Enis
dc.contributor.otherDepartment of Electrical & Electronics Engineering
dc.date.accessioned2024-07-05T14:33:01Z
dc.date.available2024-07-05T14:33:01Z
dc.date.issued2015
dc.departmentAtılım Universityen_US
dc.department-temp[Erden, Fatih] Atilim Univ, Dept Elect & Elect Engn, TR-06836 Ankara, Turkey; [Alkar, Ali Ziya] Hacettepe Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkey; [Cetin, Ahmet Enis] Bilkent Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkeyen_US
dc.descriptionErden, Fatih/0000-0002-1708-3063; Alkar, Ali Ziya/0000-0002-5880-2423en_US
dc.description.abstractIn this paper, a multi-modal solution to the people counting problem in a given area is described. The multi-modal system consists of a differential pyro-electric infrared (PIR) sensor and a camera. Faces in the surveillance area are detected by the camera with the aim of counting people using cascaded AdaBoost classifiers. Due to the imprecise results produced by the camera-only system, an additional differential PIR sensor is integrated to the camera. Two types of human motion: (i) entry to and exit from the surveillance area and (ii) ordinary activities in that area are distinguished by the PIR sensor using a Markovian decision algorithm. The wavelet transform of the continuous-time real-valued signal received from the PIR sensor circuit is used for feature extraction from the sensor signal. Wavelet parameters are then fed to a set of Markov models representing the two motion classes. The affiliation of a test signal is decided as the class of the model yielding higher probability. People counting results produced by the camera are then corrected by utilizing the additional information obtained from the PIR sensor signal analysis. With the proof of concept built, it is shown that the multi-modal system can reduce false alarms of the camera-only system and determines the number of people watching a TV set in a more robust manner. (c) 2015 Elsevier B.V. All rights reserved.en_US
dc.identifier.citationcount9
dc.identifier.doi10.1016/j.infrared.2015.07.019
dc.identifier.endpage134en_US
dc.identifier.issn1350-4495
dc.identifier.issn1879-0275
dc.identifier.scopus2-s2.0-84938824531
dc.identifier.scopusqualityQ2
dc.identifier.startpage127en_US
dc.identifier.urihttps://doi.org/10.1016/j.infrared.2015.07.019
dc.identifier.urihttps://hdl.handle.net/20.500.14411/851
dc.identifier.volume72en_US
dc.identifier.wosWOS:000362146700017
dc.identifier.wosqualityQ2
dc.institutionauthorErden, Fatih
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.scopus.citedbyCount19
dc.subjectInfrared sensorsen_US
dc.subjectMarkov modelsen_US
dc.subjectMulti-modal systemsen_US
dc.subjectPeople countingen_US
dc.titleA Robust System for Counting People Using an Infrared Sensor and a Cameraen_US
dc.typeArticleen_US
dc.wos.citedbyCount8
dspace.entity.typePublication
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