3D acquisition of archaeological heritage from images

In this contribution an approach is proposed that can capture the 3D shape and appearance of objects, monuments or sites from photographs or video. The flexibility of the approach allows us to deal with uncalibrated hand-held camera images. In addition, through the use of advanced computer vision algorithms the process is largely automated. Both these factors make the approach ideally suited to applications in archaeology. Not only does it become feasible to obtain photo-realistic virtual reconstructions of monuments and sites, but also stratigraphy layers and separate building blocks can be reconstructed. These can then be used as detailed records of the excavations or allow virtual re-assemblage of monuments. Since the motion of the camera is also computed, it also becomes possible to augment video streams of ancient remains with virtual reconstruction. The proposed approach retrieves both the structure of a scene and the motion of the camera from an image sequence. In a first step features are extracted and matched over consecutive images. This step is followed by a structurefrom-motion algorithm that yields a sparse 3D reconstruction (i.e. the matched 3D features) and the path of the camera. These results are enhanced through auto-calibration and bundle adjustment. To allow a full surface reconstruction of the observed scene, the images are rectified so that a standard stereo algorithm can be used to determine dense disparity maps. By combining several of these maps, accurate depth maps are computed. These can then be integrated together to yield a dense 3D surface model. By making use of texture mapping photo-realistic models can be obtained.

[1]  Reinhard Klette,et al.  Multi-Image Analysis , 2001, Lecture Notes in Computer Science.

[2]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[3]  Reinhard Koch,et al.  Multi Viewpoint Stereo from Uncalibrated Video Sequences , 1998, ECCV.

[4]  Lutz Falkenhagen.  Hierarchical Block-Based Disparity Estimation Considering Neighbourhood Constraints , 1997 .

[5]  Richard Szeliski,et al.  Vision Algorithms: Theory and Practice , 2002, Lecture Notes in Computer Science.

[6]  Olivier D. Faugeras,et al.  What can be seen in three dimensions with an uncalibrated stereo rig , 1992, ECCV.

[7]  Ingemar J. Cox,et al.  A Maximum Likelihood Stereo Algorithm , 1996, Comput. Vis. Image Underst..

[8]  Reinhard Koch,et al.  A simple and efficient rectification method for general motion , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[9]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[10]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[11]  KanadeTakeo,et al.  Shape and motion from image streams under orthography , 1992 .

[12]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[13]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Jitendra Malik,et al.  Modeling and Rendering Architecture from Photographs: A hybrid geometry- and image-based approach , 1996, SIGGRAPH.

[15]  Reinhard Koch,et al.  Automatische Oberflächenmodellierung starrer dreidimensionaler Objekte aus stereoskopischen Rundum-Ansichten , 1997 .

[16]  Rajiv Gupta,et al.  Stereo from uncalibrated cameras , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Reinhard Koch,et al.  Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

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

[19]  Reinhard Koch,et al.  Image-Based Rendering from Uncalibrated Lightfields with Scalable Geometry , 2000, Theoretical Foundations of Computer Vision.