3D target recognition based on projective invariant relationships
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, BS | - |
dc.contributor.author | Lee, KM | - |
dc.contributor.author | Lee, SU | - |
dc.contributor.author | Yun, ID | - |
dc.date.accessioned | 2022-03-14T07:43:58Z | - |
dc.date.available | 2022-03-14T07:43:58Z | - |
dc.date.created | 2022-03-14 | - |
dc.date.issued | 2003-03 | - |
dc.identifier.issn | 1047-3203 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/25998 | - |
dc.description.abstract | In this paper, we propose a new 3D target recognition algorithm using a single image. Our approach is based on geometrically invariant relationships. By employing a practical CCD camera model for projective image formation, and analyzing the constraints on the projection parameters, we derive two invariant relationships using six pairs of 3D space features and corresponding image features, such as points and lines. Compared to the conventional approach in which only a single invariant relationship is derived from six point pairs based on the general finite projective camera model, the two relationships obtained from the practical camera model can increase the effectiveness of matching. Based on the derived invariant relationships, a new view-invariant object recognition algorithm using a single image is proposed. The performance of the proposed recognition algorithm is demonstrated by various computer simulations on synthetic and real images of objects. The experimental results show that 3D objects in the image can be robustly recognized, using the linear features, by the proposed algorithm. (C) 2003 Elsevier Science (USA). All rights reserved. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ACADEMIC PRESS INC ELSEVIER SCIENCE | - |
dc.subject | OBJECT RECOGNITION | - |
dc.subject | POINTS | - |
dc.subject | VIEW | - |
dc.title | 3D target recognition based on projective invariant relationships | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, KM | - |
dc.identifier.doi | 10.1016/S1047-3203(02)00013-5 | - |
dc.identifier.wosid | 000182138500001 | - |
dc.identifier.bibliographicCitation | JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v.14, no.1, pp.1 - 21 | - |
dc.relation.isPartOf | JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION | - |
dc.citation.title | JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION | - |
dc.citation.volume | 14 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 21 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.subject.keywordPlus | OBJECT RECOGNITION | - |
dc.subject.keywordPlus | POINTS | - |
dc.subject.keywordPlus | VIEW | - |
dc.subject.keywordAuthor | model-based recognition | - |
dc.subject.keywordAuthor | target recognition | - |
dc.subject.keywordAuthor | invariant relationships | - |
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