Real-time processing for intelligent-surveillance applications
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sungju | - |
dc.contributor.author | Kim, Heegon | - |
dc.contributor.author | Sa, Jaewon | - |
dc.contributor.author | Park, Byungkwan | - |
dc.contributor.author | Chung, Yongwha | - |
dc.date.accessioned | 2021-09-03T07:04:32Z | - |
dc.date.available | 2021-09-03T07:04:32Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-04-25 | - |
dc.identifier.issn | 1349-2543 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/83721 | - |
dc.description.abstract | Although the typical sensor-server model has been widely used in intelligent-surveillance applications, the workload increases for the centralized server as the number of sensors increases; therefore, the provision of a scalable performance requires the distribution of the centralized-server workload into the sensors. Due to the limited resources of the sensor side, however, a resource-efficient real-time processing technique is required. In this paper, a real-time sensor-side surveillance technique for which parallel processing is used on CPU-GPU hybrid-computing devices is proposed. The experiment results reveal that the proposed method can provide a real-time execution of the surveillance system. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG | - |
dc.title | Real-time processing for intelligent-surveillance applications | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Sungju | - |
dc.contributor.affiliatedAuthor | Chung, Yongwha | - |
dc.identifier.doi | 10.1587/elex.14.20170227 | - |
dc.identifier.scopusid | 2-s2.0-85019085495 | - |
dc.identifier.wosid | 000401173800020 | - |
dc.identifier.bibliographicCitation | IEICE ELECTRONICS EXPRESS, v.14, no.8 | - |
dc.relation.isPartOf | IEICE ELECTRONICS EXPRESS | - |
dc.citation.title | IEICE ELECTRONICS EXPRESS | - |
dc.citation.volume | 14 | - |
dc.citation.number | 8 | - |
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.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordAuthor | surveillance | - |
dc.subject.keywordAuthor | real time | - |
dc.subject.keywordAuthor | Amdahl&apos | - |
dc.subject.keywordAuthor | s law | - |
dc.subject.keywordAuthor | video sensor | - |
dc.subject.keywordAuthor | CPU-GPU computing | - |
dc.subject.keywordAuthor | parallel processing | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
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.