Quick Reconstruction of Cameras and Quasi-dense Geometry from Unordered Photos

This paper presents a novel approach to quick reconstruction of cameras and quasi-dense geometry from unordered photos of a scene. With three reconstruction goals: reliable camera postures, high-density scene geometry, and a low cost of time, our approach consists of two stages: pairwise relating and two-tier reconstruction. At the first stage, to obtain better putative matches, we impose bidirectional feature matching and disparity constraint; to achieve better normalization, we perform approximate self-calibration using EXIF tag. The second stage includes a sparse and a quasi-dense reconstruction with different pivot respectively, adding selection strategies to avoid degenerate cases and improve time efficiency.

[1]  Maarten Vergauwen,et al.  Web-based 3D Reconstruction Service , 2006, Machine Vision and Applications.

[2]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[3]  Richard I. Hartley,et al.  In defence of the 8-point algorithm , 1995, Proceedings of IEEE International Conference on Computer Vision.

[4]  Olivier D. Faugeras,et al.  Complete Dense Stereovision Using Level Set Methods , 1998, ECCV.

[5]  Long Quan,et al.  A quasi-dense approach to surface reconstruction from uncalibrated images , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[7]  Richard Szeliski,et al.  Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.

[8]  Matthew A. Brown,et al.  Unsupervised 3D object recognition and reconstruction in unordered datasets , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[9]  Paul A. Beardsley,et al.  3D Model Acquisition from Extended Image Sequences , 1996, ECCV.

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

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

[12]  Sunil Arya,et al.  An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.

[13]  Luc Van Gool,et al.  Surviving Dominant Planes in Uncalibrated Structure and Motion Recovery , 2002, ECCV.

[14]  Richard I. Hartley,et al.  In Defense of the Eight-Point Algorithm , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

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