Automatic 3D surface reconstruction by combining stereovision with the slit-scanner approach

dc.contributor.author	Πρόκος, Αντώνης	el
dc.contributor.author	Καρράς, Γιώργος	el
dc.contributor.author	Πέτσα, Έλλη	el
dc.date.accessioned	2015-01-28T11:10:02Z
dc.date.available	2015-01-28T11:10:02Z
dc.date.issued	2015-01-28
dc.identifier.uri	http://hdl.handle.net/11400/4920
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Photogrammetric scanning
dc.subject	Surface reconstruction
dc.subject	Triangulation
dc.subject	Epipolar geometry
dc.subject	Camera calibration
dc.subject	Σάρωση φωτογραμμετρικών
dc.subject	Ανακατασκευή επιφάνειας
dc.subject	Τριγωνισμός
dc.subject	Επιπολική γεωμετρία
dc.subject	Βαθμονόμηση της κάμερας
dc.title	Automatic 3D surface reconstruction by combining stereovision with the slit-scanner approach	en
heal.type	conferenceItem
heal.classification	Technology
heal.classification	Photogrammetry
heal.classification	Τεχνολογία
heal.classification	Φωτογραμμετρία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://skos.um.es/unescothes/C02980
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Φωτογραμμετρία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85137410
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας, Σχολή Τεχνολογικών Εφαρμογών, Τμήμα Μηχανικών Πληροφορικής και Μηχανικών Τοπογραφίας & Γεωπληροφορικής	el
heal.publicationDate	2010
heal.bibliographicCitation	Prokos A., Karras G. and Petsa E. (2010). Automatic 3D surface reconstruction by combining stereovision with the slit-scanner approach .International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII, Part 5, pp. 505-509. Available from: http://www.isprs.org/proceedings/XXXVIII/part5/papers/93.pdf	en
heal.abstract	In this paper, a 3D surface scanner is presented. Combining stereovision and slit-scanning, our system is composed of two cameras and a hand-held laser plane. The camera pair is calibrated using synchronized image pairs of a coded chessboard; its imaged nodes are automatically identified, referred to the object points and introduced into a self-calibrating bundle adjustment. For the scanning process, stereoscopic profiles are continuously recorded as the 3D surface is swept by the laser line. After epipolar resampling of the synchronized image pairs, search for point correspondences is thus reduced to identifying intersections of image rows with the re-corded laser profiles. The maxima of Gaussian curves fitted to the gray-value data along the epipolar image rows provide initial esti-mates for peak positions, which are then refined using information from their neighbourhood. In our setup, 3D reconstruction by simple stereovision is strengthened by enforcing extra geometric constraints. First, the coplanarity constraint is imposed on all 3D points reconstructed from a single laser stripe, and the coefficients of all laser planes participate as unknowns in the 3D recon-struction adjustment. Additionally, this also allows identifying mismatches since epipolar lines may have more than one peaks; the correct 3D point is established according to a distance threshold from the laser plane. The solution is further reinforced by placing the object in a corner formed by two background planes (which are scanned along with the object), whose coefficients are also unknowns in the 3D reconstruction adjustment. The linear laser segments produced on either side of the object have to satisfy the equation of both the corresponding plane and the laser plane. Image pairs of the corner without the object (longer laser segments) are added to the dataset for a more accurate determination of plane equations. Results are presented and evaluated from this setup, whose typical accuracy is estimated in the order of 0.2 mm in 3D depth estimation.	en
heal.fullTextAvailability	true
heal.conferenceName	International Archives of Photogrammry, Remote Sensing and Spatial Information Sciences	en
heal.conferenceItemType	full paper