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Automatic Image Selection in Photogrammetric Multi-view Stereo Methods

Hosseininaveh, A; Serpico, M; Robson, S; Hess, M; Boehm, J; Pridden, I; Amati, G; (2012) Automatic Image Selection in Photogrammetric Multi-view Stereo Methods. In: Arnold, DB and Kaminski, J and Niccolucci, F and Stork, A, (eds.) VAST. (pp. 9 - 16). Eurographics Association Green open access

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Abstract

This paper brings together a team of specialists in optical metrology, museum curation, collection digitization and 3D development to describe and illustrate by example a method for the selection of the most suitable camera views, vantage viewpoints, from a large image dataset intended for metric 3D artefact reconstruction. The presented approach is capable of automatically identifying and processing the most appropriate images from a multi-image photogrammetric network captured by an imaging specialist. The aim is to produce a 3D model suited to a wide range of museum uses, including visitor interactives. The approach combines off-the-shelf imaging equipment with rigorous photogrammetric bundle adjustment and multi-view stereo (MVS), supported by an image selection process that is able to take into account range-related and visibility-related constraints. The paper focusses on the two key steps of image clustering and iterative image selection. The developed method is illustrated by the 3D recording of four ancient Egyptian artefacts from the Petrie Museum of Egyptian Archaeology at UCL, with an analysis taking into account completeness, coordination uncertainty and required number of images. Comparison is made against the baseline of the established CMVS (Clustering Views for Multi-view Stereo), which is a free package for selecting vantage images within a huge image collection. For the museum, key outputs from the 3D recording process are visitor interactives which are built around high quality textured mesh models. The paper therefore considers the quality of the output from each process as input to texture model generation. Results demonstrate that whilst both methods can provide high quality records, our new method, Image Network Designer (IND), can provide a better image selection for MVS than CMVS in terms of coordination uncertainty and completeness of the final model for the museum recording of artefacts. Furthermore, the improvements gained, particularly in model completeness, minimise the significant overhead in mesh editing needed to provide a more direct and economical route to 3D model output.

Type: Proceedings paper
Title: Automatic Image Selection in Photogrammetric Multi-view Stereo Methods
ISBN-13: 978-3-905674-39-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.2312/VAST/VAST12/009-016
Publisher version: http://dx.doi.org/10.2312/VAST/VAST12/009-016
Language: English
Additional information: This is the authors' accepted version of this published article. The definitive version is available at http://diglib.eg.org/
Keywords: Cultural heritage objects, Multi View Stereo (MVS), Structure from Motion (SfM), Close Range Photogrammetry, Imaging Network, Image Clustering and Selection, ancient Egypt, cartonnage, Hawara, Gurob
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Dept of Information Studies
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Institute of Archaeology
URI: https://discovery.ucl.ac.uk/id/eprint/1369912
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