Extracting textured vertical facades from controlled close-range imagery

We are developing a system to extract geodetic, textured CAD models from thousands of initially uncontrolled, close-range ground and aerial images of urban scenes. Here we describe one component of the system, which operates after the imagery has been controlled or geo-referenced. This fully automatic component detects significant vertical facades in the scene, then extrudes them to meet an inferred, triangulated terrain and procedurally generated roof polygons. The algorithm then estimates for each surface a computer graphics texture, or diffuse reflectance map, from the many available observations of that surface. We present the results of the algorithm on a complex dataset: nearly 4,000 high-resolution digital images of a small (200 meter square) office park, acquired from close range under highly varying lighting conditions, amidst significant occlusion due both to multiple inter-occluding structures, and dense foliage. While the results are of less fidelity than that would be achievable by an interactive system, our algorithm is the first to be demonstrated on such a large, real-world dataset.

[1]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[2]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Jake K. Aggarwal,et al.  Structure from stereo-a review , 1989, IEEE Trans. Syst. Man Cybern..

[4]  James C. Miller,et al.  Computer graphics principles and practice, second edition , 1992, Comput. Graph..

[5]  Richard Szeliski,et al.  Recovering 3D Shape and Motion from Image Streams Using Nonlinear Least Squares , 1994, J. Vis. Commun. Image Represent..

[6]  P. Anandan,et al.  Direct recovery of shape from multiple views: a parallax based approach , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[7]  Rakesh Kumar,et al.  Shape Recovery from Multiple Views: A Parallax Based Approach , 1994 .

[8]  V. Michael Bove,et al.  Semiautomatic 3-D model extraction from uncalibrated 2-D camera views , 1995 .

[9]  V. Bove,et al.  Semiautomatic 3D-model extraction from uncalibrated 2D-camera views , 1995 .

[10]  David J. Kriegman,et al.  Structure and Motion from Line Segments in Multiple Images , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Shenchang Eric Chen,et al.  QuickTime VR: an image-based approach to virtual environment navigation , 1995, SIGGRAPH.

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

[13]  Hans P. Moravec.  Robot spatial perception by stereoscopic vision and 3D evidence grids , 1996 .

[14]  Robin Liggett,et al.  Virtual Modeling of Urban Environments , 1996, Presence: Teleoperators & Virtual Environments.

[15]  Richard Szeliski,et al.  Video mosaics for virtual environments , 1996, IEEE Computer Graphics and Applications.

[16]  Richard Szeliski,et al.  3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Robert T. Collins,et al.  A space-sweep approach to true multi-image matching , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Richard Szeliski,et al.  Creating full view panoramic image mosaics and environment maps , 1997, SIGGRAPH.

[19]  Seth J. Teller,et al.  Acquisition of a large pose-mosaic dataset , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[20]  Andrew Zisserman,et al.  Automatic reconstruction of piecewise planar models from multiple views , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).