Recovering building structures from stereo

Addresses the problem of extracting polyhedral building structures from a stereo pair of aerial intensity images. The authors describe a system that computes a hierarchy of descriptions such as segments, junctions, and links between junctions from each view, and matches these features at the different levels. Such high level features not only help reduce correspondence ambiguity during stereo matching, but also allow us to infer surface boundaries even though the boundaries may be broken because of noise and weak contrast. The authors hypothesize surface boundaries by examining global information such as continuity and coplanarity of linked edges in 3-D, rather than merely by looking at local depth information. When the walls of the buildings are visible, they also exploit the relationship among adjacent surfaces in a polyhedral object to help confirm the different levels of descriptions. The authors give some experimental results for aerial images taken from overhead views and oblique views.<<ETX>>

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

[2]  Yuan C. Hsieh,et al.  Performance Evaluation of Scene Registration and Stereo Matching for Artographic Feature Extraction , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  G. Medioni,et al.  Accurate surface description from binocular stereo , 1989, [1989] Proceedings. Workshop on Interpretation of 3D Scenes.

[4]  Ramakant Nevatia,et al.  Using Perceptual Organization to Extract 3-D Structures , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  T. Kanade,et al.  The 3D MOSAIC scene understanding system: incremental reconstruction of 3D scenes for complex images , 1987 .

[6]  K. Ramesh Babu,et al.  Linear Feature Extraction and Description , 1979, IJCAI.

[7]  R. Nevatia,et al.  Use of monocular groupings and occlusion analysis in a hierarchical stereo system , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Narendra Ahuja,et al.  Surfaces from Stereo: Integrating Feature Matching, Disparity Estimation, and Contour Detection , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Eric L. W. Grimson,et al.  From Images to Surfaces: A Computational Study of the Human Early Visual System , 1981 .

[10]  Pascal Fua,et al.  Objective functions for feature discrimination: applications to semiautomated and automated feature extraction , 1989 .

[11]  Tomaso A. Poggio,et al.  On parallel stereo , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[12]  Demetri Terzopoulos,et al.  Regularization of Inverse Visual Problems Involving Discontinuities , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Ramakant Nevatia,et al.  Segment-based stereo matching , 1985, Comput. Vis. Graph. Image Process..

[14]  Jitendra Malik,et al.  Progress in Stereo Mapping , 1983 .

[15]  Sidney Liebes,et al.  Geometric Constraints For Interpreting Images Of Common Structural Elements: Orthogonal Trihedral Vertices , 1981, Other Conferences.

[16]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.