VISIRE: photorealistic 3D reconstruction from video sequences

Traditionally, building 3D reconstructions of large scenarios such as a museum or historical site has been costly, time consuming and required the contribution of expert personnel. Usually the results showed an artificial look and had little interactivity. However, newly developed technologies in the areas of video analysis, camera calibration and texture fusion allow us to think in a much more satisfying scenario where the user with the only aid of a domestic video camera is able to acquire all the information it is required to construct the 3D model of the desired environment in an easy and comfortable manner. In this paper, the results obtained in the EC funded project VISIRE are presented. VISIRE attempts to construct photorealistic 3D models of large scenarios using as input multiple freehand video sequences. Once acquired, the computer vision software processes the video information off-line in order to obtain the 3D mesh together with the textures required to obtain a 3D model highly resembling the original.

[1]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[2]  Anders Heyden,et al.  Euclidean reconstruction from image sequences with varying and unknown focal length and principal point , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Edmond Boyer,et al.  Regular and non-regular point sets: Properties and reconstruction , 2001, Comput. Geom..

[4]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

[5]  Cordelia Schmid,et al.  Appariement d'images par invariants locaux de niveaux de gris. Application à l'indexation d'une base d'objets. (Image matching by local greyvalue invariants. Applied to indexing an object database) , 1996 .

[6]  Andrew W. Fitzgibbon,et al.  Bundle Adjustment - A Modern Synthesis , 1999, Workshop on Vision Algorithms.

[7]  Takeo Kanade,et al.  Image-consistent surface triangulation , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[8]  Adrian Hilton,et al.  Reconstruction of scene models from sparse 3D structure , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).