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dc.contributor.authorZia, Ali
dc.contributor.authorLiang, Jie
dc.contributor.authorZhou, Jun
dc.contributor.authorGao, Yongsheng
dc.contributor.editorSudeep Sarkar, Subhodev Das, Bahram Parvin, Fatih Porikli
dc.date.accessioned2017-05-03T16:11:36Z
dc.date.available2017-05-03T16:11:36Z
dc.date.issued2015
dc.identifier.isbn9781479966820
dc.identifier.issn2472-6737
dc.identifier.doi10.1109/WACV.2015.49
dc.identifier.urihttp://hdl.handle.net/10072/69688
dc.description.abstract3D reconstruction from hyper spectral images has seldom been addressed in the literature. This is a challenging problem because 3D models reconstructed from different spectral bands demonstrate different properties. If we use a single band or covert the hyper spectral image to gray scale image for the reconstruction, fine structural information may be lost. In this paper, we present a novel method to reconstruct a 3D model from hyper spectral images. Our proposed method first generates 3D point sets from images at each wavelength using the typical structure from motion approach. A structural descriptor is developed to characterize the spatial relationship between the points, which allows robust point matching between two 3D models at different wavelength. Then a 3D registration method is introduced to combine all band-level models into a single and complete hyper spectral 3D model. As far as we know, this is the first attempt in reconstructing a complete 3D model from hyper spectral images. This work allows fine structural-spectral information of an object be captured and integrated into the 3D model, which can be used to support further research and applications.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent6145945 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers
dc.publisher.placeUnited States
dc.publisher.urihttp://wacv2015.org/
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofconferencenameIEEE Winter Conference on Applications of Computer Vision (WACV 2015)
dc.relation.ispartofconferencetitle2015 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV)
dc.relation.ispartofdatefrom2015-01-06
dc.relation.ispartofdateto2015-01-09
dc.relation.ispartoflocationWaikoloa, HI
dc.relation.ispartofpagefrom318
dc.relation.ispartofpagefrom8 pages
dc.relation.ispartofpageto325
dc.relation.ispartofpageto8 pages
dc.rights.retentionY
dc.subject.fieldofresearchComputer vision
dc.subject.fieldofresearchcode460304
dc.title3D Reconstruction from Hyperspectral Images
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorZhou, Jun


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    Contains papers delivered by Griffith authors at national and international conferences.

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