Metric 3D reconstruction and texture acquisition of surfaces of revolution from a single uncalibrated view

Image analysis and computer vision can be effectively employed to recover the three-dimensional structure of imaged objects, together with their surface properties. In this paper, we address the problem of metric reconstruction and texture acquisition from a single uncalibrated view of a surface of...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 27(2005), 1 vom: 10. Jan., Seite 99-114
1. Verfasser: Colombo, Carlo (VerfasserIn)
Weitere Verfasser: Del Bimbo, Alberto, Pernici, Federico
Format: Aufsatz
Sprache:English
Veröffentlicht: 2005
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study
LEADER 01000naa a22002652 4500
001 NLM152899790
003 DE-627
005 20231223062941.0
007 tu
008 231223s2005 xx ||||| 00| ||eng c
028 5 2 |a pubmed24n0510.xml 
035 |a (DE-627)NLM152899790 
035 |a (NLM)15628272 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Colombo, Carlo  |e verfasserin  |4 aut 
245 1 0 |a Metric 3D reconstruction and texture acquisition of surfaces of revolution from a single uncalibrated view 
264 1 |c 2005 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 01.02.2005 
500 |a Date Revised 10.12.2019 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a Image analysis and computer vision can be effectively employed to recover the three-dimensional structure of imaged objects, together with their surface properties. In this paper, we address the problem of metric reconstruction and texture acquisition from a single uncalibrated view of a surface of revolution (SOR). Geometric constraints induced in the image by the symmetry properties of the SOR structure are exploited to perform self-calibration of a natural camera, 3D metric reconstruction, and texture acquisition. By exploiting the analogy with the geometry of single axis motion, we demonstrate that the imaged apparent contour and the visible segments of two imaged cross sections in a single SOR view provide enough information for these tasks. Original contributions of the paper are: single view self-calibration and reconstruction based on planar rectification, previously developed for planar surfaces, has been extended to deal also with the SOR class of curved surfaces; self-calibration is obtained by estimating both camera focal length (one parameter) and principal point (two parameters) from three independent linear constraints for the SOR fixed entities; the invariant-based description of the SOR scaling function has been extended from affine to perspective projection. The solution proposed exploits both the geometric and topological properties of the transformation that relates the apparent contour to the SOR scaling function. Therefore, with this method, a metric localization of the SOR occluded parts can be made, so as to cope with them correctly. For the reconstruction of textured SORs, texture acquisition is performed without requiring the estimation of external camera calibration parameters, but only using internal camera parameters obtained from self-calibration 
650 4 |a Comparative Study 
650 4 |a Evaluation Study 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Validation Study 
700 1 |a Del Bimbo, Alberto  |e verfasserin  |4 aut 
700 1 |a Pernici, Federico  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 27(2005), 1 vom: 10. Jan., Seite 99-114  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:27  |g year:2005  |g number:1  |g day:10  |g month:01  |g pages:99-114 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 27  |j 2005  |e 1  |b 10  |c 01  |h 99-114