Given a set of unorganized images taken from unknown viewpoints and directions, the proposed method  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.
Reconstructions of the sparse correspondences were obtained using method  and the dense reconstructions using methods ,  and .
Fully automatic data processing pipeline : 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 . Image pairs suitable for dense matching are automatically selected, rectified and used in dense binocular matching . The dense point cloud obtained as the union of all pairwise reconstructions is fused by a local approximation using oriented geometric primitives . For texturing, every primitive is mapped on the image with the best resolution.
This research was supported by The Czech Academy of Sciences under project 1ET101210406 and by the EU project IST-2001-39184. Andrew Zisserman from the University of Oxford kindly provided the Dinosaur data, Tomáš Werner from the Czech Technical University provided the routine for the bundle adjustment.
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