Distributed eigenfaces for massive face image data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Jeong-Keun | - |
dc.contributor.author | Park, Ho-Hyun | - |
dc.contributor.author | Park, Jaehwa | - |
dc.date.available | 2019-03-08T07:36:35Z | - |
dc.date.issued | 2017-12 | - |
dc.identifier.issn | 1380-7501 | - |
dc.identifier.issn | 1573-7721 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/3559 | - |
dc.description.abstract | The assumption that the number of training samples is less than the number of pixels in a face image is essential for conventional eigenface-based face recognition. But recently, it has become impractical for massive face image collections. A parallel processing method using distributed eigenfaces is presented. A massive face image set was divided into a bunch of small subsets that satisfied the assumption of conventional approaches. Eigenfaces were extracted from the subsets and stored in a cloud system. Face recognition was performed by parallel processing using the distributed eigenfaces in the cloud system. A face recognition system was implemented in the Hadoop system. Various experiments were performed to test the validity of the distributed eigenface-based approach. The experimental results show that, compared to conventional methods, the implemented distributed face recognition system worked well for large datasets without significant performance degradation. | - |
dc.format.extent | 18 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER | - |
dc.title | Distributed eigenfaces for massive face image data | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s11042-017-4823-6 | - |
dc.identifier.bibliographicCitation | MULTIMEDIA TOOLS AND APPLICATIONS, v.76, no.24, pp 25983 - 26000 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000417633500023 | - |
dc.identifier.scopusid | 2-s2.0-85019584624 | - |
dc.citation.endPage | 26000 | - |
dc.citation.number | 24 | - |
dc.citation.startPage | 25983 | - |
dc.citation.title | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.volume | 76 | - |
dc.type.docType | Article | - |
dc.publisher.location | 네델란드 | - |
dc.subject.keywordAuthor | Eigenface | - |
dc.subject.keywordAuthor | Face recognition | - |
dc.subject.keywordAuthor | Parallel processing | - |
dc.subject.keywordAuthor | Hadoop | - |
dc.subject.keywordPlus | PRINCIPAL COMPONENT ANALYSIS | - |
dc.subject.keywordPlus | RECOGNITION | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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