Robust Rotation and Translation Estimation in Multiview Reconstruction

CVPR'07 Demo

Daniel Martinec, Tomáą Pajdla, Jan Čech, and Radim ©ára
Center for Machine Perception, Czech Technical University in Prague


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.
Click on an image
to see a 3D model

Animations will be seen, e.g.,
in Cortona VRML Client
under Windows and freewrl
under Linux.
St. Martin rotunda

124 img [1200x900]
distinguished regions (DR)
99.24% occlusions
download images*
Raglan castle

46 img [759x1106]
DR
98.30% occlusions
images at Oxford
Tête de Plate Longe

257 img [900x1200]
DR
99.68% occlusions
download images*
*   Please cite paper [1] in work that uses the images.

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 a large amount of occlusions, mismatches, and non-existent pair-wise geometries [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, by the EU projects eTRIMS FP6-IST-027113 and DIRAC FP6-IST-027787, and by MSM6840770038 DMCM III. Jan Čech from the Czech Technical University provided routines for dense stereo [2]. 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. Robust Rotation and Translation Estimation in Multiview Reconstruction. CVPR 2007, IEEE, Minneapolis, MN, USA, June 2007. CD-ROM. (poster)

[2] J. Čech and R. ©ára. Efficient Sampling of Disparity Space for Fast and Accurate Matching. In Proc. BenCOS Workshop CVPR, 2007.

[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)