Implementing an adaptive approach for dense stereo-matching

dc.contributor.author	Στεντούμης, Χρήστος	el
dc.contributor.author	Γραμματικόπουλος, Λάζαρος	el
dc.contributor.author	Καλησπεράκης, Ηλίας	el
dc.contributor.author	Καρράς, Γιώργος	el
dc.date.accessioned	2015-01-28T09:19:49Z
dc.date.available	2015-01-28T09:19:49Z
dc.date.issued	2015-01-28
dc.identifier.uri	http://hdl.handle.net/11400/4908
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.source	http://portal.survey.ntua.gr/main/labs/photo/staff/gkarras/Karras_ISPRS_2012a.pdf	en
dc.subject	Matching
dc.subject	Correlation
dc.subject	Surface
dc.subject	Reconstruction
dc.subject	Point cloud
dc.subject	Ταίριασμα
dc.subject	Επιφάνεια
dc.subject	Ανακατασκευή
dc.title	Implementing an adaptive approach for dense stereo-matching	en
heal.type	conferenceItem
heal.classification	Photogrammetry--Digital techniques
heal.classification	Φωτογραμμετρία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh2006001819
heal.classificationURI	N/A-Φωτογραμμετρία
heal.language	en
heal.access	free
heal.recordProvider	Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Πολιτικών Μηχανικών Τ.Ε. και Μηχανικών Τοπογραφίας και Γεωπληροφορικής. Κατεύθυνση Πολιτικών Μηχανικών Τ.Ε.	el
heal.publicationDate	2012
heal.bibliographicCitation	C. Stentoumis, L. Grammatikopoulos, I. Kalisperakis, G. Karras. 2012. Implementing an adaptive approach for dense stereo-matching. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.38, part 5	el
heal.abstract	Defining pixel correspondences in stereo-pairs is a fundamental process in automated image-based 3D reconstruction. In this contribution we report on an approach for dense matching, based on local optimization. The approach represents a fusion of state-of-theart algorithms and novel considerations, which mainly involve improvements in the cost computation and aggregation processes. The matching cost which has been implemented here combines the absolute difference of image colour values with a census transformation directly on images gradient of all colour channels. Besides, a new cost volume is computed by aggregating over cross-window support regions with a linearly defined threshold on cross-window expansion. Aggregated costs are, then, refined using a scan-line optimization technique, and the disparity map is estimated using a ‘winner-takes-all’ selection. Occlusions and mismatches are also handled using existing schemes. The proposed algorithm is tested on a standard stereo-matching data-set with promising results. The future tasks mainly include research on refinement of the disparity map and development of a self-adaptive approach for weighting the contribution of different matching cost components.	en
heal.fullTextAvailability	true
heal.conferenceName	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences	en
heal.conferenceItemType	full paper