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Towards complete free-form reconstruction of complex 3D scenes from an unordered set of uncalibrated images
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
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2004 (English)In: STATISTICAL METHODS IN VIDEO PROCESSING / [ed] Comaniciu, D; Kanatani, K; Mester, R; Suter, D, BERLIN: SPRINGER , 2004, Vol. 3247, 1-12 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a method for accurate dense reconstruction of a complex scene from a small set of high-resolution unorganized still images taken by a hand-held digital camera. A fully automatic data processing pipeline is proposed. Highly discriminative features are first detected in all images. Correspondences are then found in all image pairs by wide-baseline stereo matching and used in a scene structure and camera reconstruction step that can cope with occlusion and outliers. Image pairs suitable for dense matching are automatically selected, rectified and used in dense binocular matching. The dense point cloud obtained as the union of all pairwise reconstructions is fused by local approximation using oriented geometric primitives. For texturing, every primitive is mapped on the image with the best resolution. The global structure reconstruction in the first step allows us to work with an unorganized set of images and to avoid error accumulation. By using object-centered geometric primitives we are able to preserve the flexibility of the method to describe complex free-form structures, preserve the possibility to build the dense model in an incremental way, and to retain the possibility to refine the cameras and the dense model by bundle adjustment. Results are demonstrated on partial models of a circular church and a Henri de Miller's sculpture. We observed spatial resolution in the range of centimeters on objects of about 20 m in size.

Place, publisher, year, edition, pages
BERLIN: SPRINGER , 2004. Vol. 3247, 1-12 p.
Series
LECTURE NOTES IN COMPUTER SCIENCE, ISSN 0302-9743 ; 3247
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-43963ISI: 000227348500001Scopus ID: 2-s2.0-33845431537ISBN: 3-540-23989-8 (print)OAI: oai:DiVA.org:kth-43963DiVA: diva2:450979
Conference
2nd International Workshop on Statistical Methods in Video Processing. Prague, CZECH REPUBLIC. MAY 16, 2004
Note

QC 20111024

Available from: 2011-10-24 Created: 2011-10-19 Last updated: 2017-03-01Bibliographically approved

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Citation style
  • apa
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