Given a set of unorganized images taken from unknown viewpoints
and directions, the proposed method [1] estimates camera
positions. Such automatic calibration
makes it possible to compute an accurate 3D model of the object. The
only assumption is a sufficient overlap between some image pairs.
|
| Head2  26 images [1136x852] distinguished regions
(DR) 91.21% occlusions
Tree  23 img [1413x942]
DR 96.88% occlusions
Detenice fountain  54 img [1200x900]
DR 98.43% occlusions
Daliborka tower  64 images [1100x850] DR 96.02% occlusions
ICCV'05 Contest finals  38 images [1120x840] DR 94.05% occlusions
St. Martin rotunda  104 images [972x1296] DR 96.55% occlusions
| | | | | |
Reconstructions of the sparse correspondences were obtained using
method [1] and the dense reconstructions using methods [2], [3], and [4].
Fully automatic data processing pipeline [4]: 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
occlusions and outliers [1]. Image pairs suitable for dense matching
are automatically selected, rectified and used in dense binocular
matching [2]. The dense point cloud obtained as the union of all
pairwise reconstructions is fused by a local approximation using
oriented geometric primitives [3]. For texturing, every primitive is
mapped on the image with the best resolution.
Acknowledgements
This research was supported by The Czech Academy of
Sciences under project 1ET101210406 and by the EU projects eTRIMS
FP6-IST-027113 and DIRAC FP6-IST-027787. Richard Szeliski from
Microsoft Research provided the ICCV'05 Contest data. Jana Kostková
from the Czech Technical University provided routines for dense
stereo. Our bundle adjustment routine was based on publicly
available software
by M.I.A. Lourakis and A.A. Argyros. Frederik Schaffalitzki provided
the code for the six-point algorithm. Ondřej Chum provided the code
for epipolar geometry estimation unaffected by a dominant plane.
References
[1]
D. Martinec and T. Pajdla. 3D Reconstruction by Gluing Pair-wise Euclidean
Reconstructions, or ``How to Achieve a
Good Reconstruction from Bad
Images''. 3DPVT
2006, University of North Carolina, Chapel Hill, USA, June 2006.
[2] J. Kostková and R. ©ára. Stratified Dense Matching for Stereopsis in
Complex Scenes. In BMVC 2003: Proceedings of the
14th British Machine Vision Conference, volume 1, pages 339-348,
Norwich, UK, September 2003.
[3] R. ©ára and R. Bajcsy. Fish-Scales: Representing
Fuzzy Manifolds. Proc. IEEE Conf. ICCV
'98, pp. 811-817, Bombay, India, January 1998.
[4] H. Cornelius, R. ©ára, D. Martinec, T. Pajdla,
O. Chum, J. Matas. Towards Complete
Free-Form Reconstruction of Complex
3D Scenes from an Unordered Set of Uncalibrated
Images. SMVP/ECCV 2004, vol. LNCS
3247, pp. 1-12, Prague, Czech Republic, May 2004. (presentation)
