3D Shape Reconstruction by Using Vanishing Points

This paper investigates the quantitative reconstruction of the 3D structure of a scene from a line drawing, by using the geometrical constraints provided by the location of vanishing points. The additional information on vanishing points allows the design of an algorithm which has several advantages with respect to the usual approach based on a reduction to linear programming (Sugihara, 1982). These advantages range from a lower computational complexity to error tolerance and exact reconstruction of the 3D-geometry of the objects. These features make the algorithm a useful tool for the quantitative analysis of real-world images, which is useful for several tasks from scene understanding to automatic vehicle guidance.

[1]  T. Pavlidis.  Algorithms for Graphics and Image Processing , 1981, Springer Berlin Heidelberg.

[2]  Keiichiro Kadono,et al.  Context-constrained matching of hierarchical CAD-based models for outdoor scene interpretation , 1991, [1991 Proceedings] Workshop on Directions in Automated CAD-Based Vision.

[3]  Joseph JáJá,et al.  An Introduction to Parallel Algorithms , 1992 .

[4]  C. Coelho,et al.  Extraction of vanishing points from images of indoor and outdoor scenes , 1993, Image Vis. Comput..

[5]  Richard J. Lipton,et al.  Linear Programming is Log-Space Hard for P , 1979, Inf. Process. Lett..

[6]  Theo Pavlidis,et al.  Algorithms for Graphics and Imag , 1983 .

[7]  M. B. Clowes,et al.  On Seeing Things , 1971, Artif. Intell..

[8]  Vincent Torre,et al.  On the Complexity of Labeling Perspective Projections of Polyhedral Scenes , 1994, Artif. Intell..

[9]  A. Macworth.  Interpreting pictures of polyhedral scenes , 1973 .

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

[11]  Beatrice Brillault-O'Mahony,et al.  New method for vanishing point detection , 1991, CVGIP Image Underst..

[12]  Takeo Kanade,et al.  From a Real Chair to a Negative Chair , 1993, Artif. Intell..

[13]  Christos H. Papadimitriou,et al.  The complexity of recognizing polyhedral scenes , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[14]  David L. Waltz,et al.  Understanding Line drawings of Scenes with Shadows , 1975 .

[15]  Kokichi Sugihara,et al.  A Necessary and Sufficient Condition for a Picture to Represent a Polyhedral Scene , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  C. Coelho,et al.  The Recovery and Understanding of a Line Drawing from Indoor Scenes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Richard M. Karp,et al.  Parallel Algorithms for Shared-Memory Machines , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.

[18]  Takeo Kanade,et al.  A Theory of Origami World , 1979, Artif. Intell..

[19]  Jitendra Malik,et al.  Interpreting line drawings of curved objects , 1986, International Journal of Computer Vision.

[20]  Long Quan,et al.  Determining perspective structures using hierarchical Hough transform , 1989, Pattern Recognit. Lett..

[21]  Jake K. Aggarwal,et al.  Determining vanishing points from perspective images , 1984, Comput. Vis. Graph. Image Process..

[22]  Stephen T. Barnard,et al.  Interpreting Perspective Image , 1983, Artif. Intell..

[23]  B. Caprile,et al.  Using vanishing points for camera calibration , 1990, International Journal of Computer Vision.

[24]  Marco Straforini,et al.  Visual Routines For Outdoor Navigation , 1993, Proceedings of the Intelligent Vehicles '93 Symposium.