Robust Photo-topography by Fusing Shape-from-Shading and Stereo

Methods for fusing two computer vision methods are discussed and several example algorithms are presented to illustrate the variational method of fusing algorithms. The example algorithms seek to determine planet topography given two images taken from two different locations with two different lighting conditions. The algorithms each employ a single cost function that combines the computer vision methods of shape-from-shading and stereo in different ways. The algorithms are closely coupled and take into account all the constraints of the photo-topography problem. The algorithms are run on four synthetic test image sets of varying difficulty.

[1]  Jake K. Aggarwal,et al.  Thermal and visual information fusion for outdoor scene perception , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[2]  Stelios C. A. Thomopoulos Sensor integration and data fusion , 1990, J. Field Robotics.

[3]  L. Pau Knowledge representation approaches in sensor fusion , 1989, Autom..

[4]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[5]  Katsushi Ikeuchi,et al.  Numerical Shape from Shading and Occluding Boundaries , 1981, Artif. Intell..

[6]  Richard Szeliski,et al.  Fast shape from shading , 1990, CVGIP Image Underst..

[7]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[8]  R. Courant Methods of mathematical physics, Volume I , 1965 .

[9]  Jake K. Aggarwal,et al.  Multiple Sensor Integration/Fusion Through Image Processing: A Review , 1986 .

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

[11]  C. Weitz,et al.  Oberon: Color photometry from voyager and its geological implications , 1991 .

[12]  B. Saxberg A Modern Differential Geometric Approach to Shape from Shading , 1989 .

[13]  W. Eric L. Grimson,et al.  Binocular shading and visual surface reconstruction , 1984, Comput. Vis. Graph. Image Process..

[14]  P. Davis,et al.  Photoclinometry: Analysis of Inherent Errors and Implications for Topographic Measurements , 1984 .

[15]  Allen M. Waxman,et al.  Binocular Image Flows: Steps Toward Stereo-Motion Fusion , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Scott Y. Harmon,et al.  Sensor data fusion through a distributed blackboard , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[17]  Rui J. P. de Figueiredo,et al.  Fusion of radar and optical sensors for space robotic vision , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[18]  John M. Richardson,et al.  Fusion of Multisensor Data , 1988, Int. J. Robotics Res..

[19]  A. Brandt,et al.  Multigrid Solutions to Elliptic Flow Problems , 1979 .

[20]  Michael A. Gennert,et al.  A computational framework for understanding problems in stereo vision , 1987 .

[21]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[22]  Joe R. Brown,et al.  Comparison of neural network classifiers to quadratic classifiers for sensor fusion , 1991 .

[23]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Laurence S. Wilson,et al.  Photoclinometry of Terrestrial and Planetary Surfaces , 1985 .

[25]  Aaron F. Bobick,et al.  The direct computation of height from shading , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[26]  Larry H. Matthies,et al.  Integration of sonar and stereo range data using a grid-based representation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[27]  Christian Heipke,et al.  Integration of Digital Image Matching and Multi Image Shape from Shading , 1992, DAGM-Symposium.

[28]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[29]  R. Kirk,et al.  I. Thermal Evolution of Ganymede and Implications for Surface Features. II. Magnetohydrodynamic Constraints on Deep Zonal Flow in the Giant Planets. III. A Fast Finite-Element Algorithm for Two-Dimensional Photoclinometry , 1987 .

[30]  P. L. Bogler,et al.  Shafer-dempster reasoning with applications to multisensor target identification systems , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[31]  David B. Cooper,et al.  Bayesian estimation of 3D surfaces from a sequence of images , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[32]  Richard Szeliski,et al.  Fast Surface Interpolation Using Hierarchical Basis Functions , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Laurence A. Soderblom,et al.  Modeling crater topography and albedo from monoscopic Viking Orbiter images: 1. Methodology , 1984 .

[34]  Robert L. Wildey,et al.  Generalized Photoclinometry for Mariner 9 , 1975 .

[35]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[36]  Mark Carlotto,et al.  A method for shape-from-shading using multiple images acquired under different viewing and lighting conditions , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[37]  Michael J. Brooks,et al.  The variational approach to shape from shading , 1986, Comput. Vis. Graph. Image Process..

[38]  R. Keys Cubic convolution interpolation for digital image processing , 1981 .

[39]  A.H. Haddad,et al.  Applied optimal estimation , 1976, Proceedings of the IEEE.

[40]  Gongzhu Hu,et al.  Fusion of gray scale and light striping in 2-D feature extraction , 1990, IEA/AIE '90.

[41]  A. McEwen Photometric functions for photoclinometry and other applications , 1991 .