Robust People Counting System Based on Sensor Fusion
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dan, Byoung-Kyu | - |
dc.contributor.author | Kim, You-Sun | - |
dc.contributor.author | Suryanto | - |
dc.contributor.author | Jung, June-Young | - |
dc.contributor.author | Ko, Sung-Jea | - |
dc.date.accessioned | 2021-09-06T17:22:57Z | - |
dc.date.available | 2021-09-06T17:22:57Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012-08 | - |
dc.identifier.issn | 0098-3063 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/107854 | - |
dc.description.abstract | This paper presents a novel robust people counting system based on fusing the depth and vision data. Conventional algorithms utilize the monoscopic or stereoscopic vision data to count people. However, these vision-based people counting methods often fail due to occasional illumination change and crowded environment. In the proposed algorithm, both the top-view vision and depth images are captured by a video-plus-depth camera mounted on the ceiling. The depth image is first processed by a morphological operator to alleviate depth artifacts such as the optical noise and lost data. Then the human object is extracted using a human model from the preprocessed depth image. Finally, the trajectory of the detected object is established by applying the bidirectional matching algorithm. Experimental results show that the proposed algorithm achieves over 98% accuracy in various testing environments(1). | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Robust People Counting System Based on Sensor Fusion | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ko, Sung-Jea | - |
dc.identifier.doi | 10.1109/TCE.2012.6311350 | - |
dc.identifier.scopusid | 2-s2.0-84867327772 | - |
dc.identifier.wosid | 000309462400040 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, v.58, no.3, pp.1013 - 1021 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON CONSUMER ELECTRONICS | - |
dc.citation.title | IEEE TRANSACTIONS ON CONSUMER ELECTRONICS | - |
dc.citation.volume | 58 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 1013 | - |
dc.citation.endPage | 1021 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Surveillance system | - |
dc.subject.keywordAuthor | people counting | - |
dc.subject.keywordAuthor | depth camera | - |
dc.subject.keywordAuthor | sensor fusing | - |
dc.subject.keywordAuthor | object detection | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.