References
- Barnard S. Stochastic stereo matching over scale. Int. J. Computer Vision 1989; 3: 17–33
- Barnard S T, Fishler M A. Computational stereo. ACM Comput. Surveys 1982; 143: 553–72
- Bayes T. An essay towards solving a problem in the doctrine of chances. Phil. Trans R. Soc. 1783; 53: 370–418
- Blake A. The least disturbance principle and weak constraints. Pattern Recog. Lett. 1983; 1: 393–9
- Bülthoff H H, Fahle M. Disparity gradients and depth scaling Report. Artificial Intelligence Laboratory, MIT. 1989, AI TR no 1175
- Bülthoff H H, Fahle M, Wegmann M. Disparity gradients and depth scaling. Perception 1991; 20: 145–63
- Bülthoff H H, Mallot H A. Interaction of different modules in depth perception. Proc. 1st Int. Conf. on Computer Vision. 1987; 295-305
- Bülthoff H H, Mallot H A. Interaction of depth modules: stereo and shading. Harvard Robotics Laboratory 1990; 1749–58, Technical Report
- Bülthoff H H, Yuille A. Bayesian models for seeing shapes and depth. Harvard Robotics Laboratory. 1990; 90–11, Technical Report
- Burt P, Julesz B. A disparity gradient limit for binocular fusion. Science 1980; 208: 615–7
- Cernushi-Frias B, Cooper D B, Hung Y-P, Belhumeur P N. Towards a model-based Bayesian theory for estimating and recognizing parameterized 3D objects using two or more images taken from different positions. IEEE Trans. Pattern Anal. Machine Intell. 1989; PAM-11: 1028–52
- Clark J, Yuille A. Data Fusion for Sensory Information Processing Systems. Kluwer Academic, Boston, MA 1990
- Dev P. Perception of depth surfaces in random-dot stereograms: A neural model. Int. J. Man-Machine Stud. 1975; 7: 511–28
- Durbin R, Willshaw D. An analog approach to the travelling salesman problem using an elastic net method. Nature 1989; 326: 689–91
- Frisby J. Computational Models of Visual Processing, M Landy, A Houshen. MIT Press, Cambridge, MA 1991
- Geiger D, Girosi F. Parallel and deterministic algorithms from MRFs :integration and surface reconstruction. IEEE Trans. Pattern Anal. Machine Intell. 1991; PAM-13: 401–12
- Geiger D, Yuille A. A common framework for image segmentation. Int. J. Computer Vision 1991; 6: 227–33
- Gelb A. Applied Optical Estimation. MIT Press, Cambridge, MA 1974
- Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of Images. IEEE Trans. on Pattern Anal. Machine Intell. 1984; PAM-6: 721–41
- Gennert M. A computational framework for understanding problems in stereo vision. PhD thesis. MIT. 1987
- Gennert M, Ren B, Yuille A L (1990) Stereo matching by energy function minimization. Proc. SPIE Visual Communications and Image Processing. Boston, November, 1990. 1383
- Grimason W E L. From Images to Surfaces. MIT Press, Cambridge, MA 1981
- Hopfield H J, Tank D W. Neural computation of decisions in optimization problems. Biological Cybernetics 1985; 52: 141–52
- Horn B K P. Robot Vision. MIT Press, Cambridge, MA 1986
- Kirkpatrick S, Gelatt C D, Vecchi M P. Optimization by simulated annealing. Science 1983; 220: 671–80
- Marr D. Vision. Freeman, San Francisco, CA 1982
- Marr D, Poggio T. Cooperative computation of stereo disparity. Science 1976; 194: 283–7
- Marr D, Poggio T. A computational theory of human stereo vision. Proc. R Soc. 1979; B 204: 301–28
- Metropolis N, Rosenbluth A, Rosenbluth M, Teller A, Teller E. Equation of state calculations by fast computing machines. J. Phys. Chem. 1953; 21: 1087–91
- Mitchison G J. Planarity and segmentation in stereoscopic matching. Perception 1988; 17: 753–82
- Mitchison G J, McKee S. The resolution of ambiguous stereoscopic matches by interpolation. Vision Res. 1987; 27: 285–94
- Mitchison G J, Westheimer. Vision: Coding and efficiency, C Blakemore. Cambridge University Press, Cambridge 1988
- Mumford D, Shah J. Optimal approximation of piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 1989; 42: 577–685
- Paris G. Statistical Field Theory. Addison-Wesley, Reading, MA 1988
- Peterson C, Söderberg B. A new method for mapping optimization problems onto neural networks. Int. J. Neural Systems. 1989; 1: 3–22
- Poggio T, Torre V, Koch C. Computational vision and regularization theory. Nature 1985; 317: 314–9
- Pollard S B, Mayhew J E W, Frisby J P. A stereo correspondence algorithm using a disparity gradient limit. Perception 1985; 14: 449–70
- Prazdny K. Detection of binocular disparities. Biol. Cybern. 1985; 52: 93–9
- Rogers B J, Graham M E. Anisotropies in the perception of three-dimensioanal surfaces. Science 1983; 221: 1409–11
- Seagrim G N. Stereoscopic vision and aniseikonic lenses I. Br J Psych. 1967; 58: 337–50
- Simic P. Statistical mechanics as the underlying theory of 'elastic' and 'neural' optimization. Network 1990; 1: 89–103
- Terzopoulos D. Multilevel computational processes for visual surface reconstruction. Comput. Vision, Graphics Image Processing 1983; 24: 52–96
- Ullman S. The Interpretation of Visual Motion. MIT Press, Cambridge, MA 1979
- Yuille A L. Energy functions for early vision and analog networks. Biol. Cybern 1989; 61: 115–23
- Yuille A L. Generalized deformable models, statistical physics, and matching problems. Neural Comput. 1990; 2: 1–24
- Yuille A, Geiger D, Bulthoff H H. Stereo integration, mean field theory and psychophysics. Harvard Robotics Laboratory. 1989; 89–11, Technical Report
- Yuille A L, Grzywacz N M. A winner-take-all mechanism based on presynaptic intitbition feedback. Neural Comput. 1989; 1: 334–47
- Yuille A, Yang T, Geiger D. Robust statistics, transparency and correspondence. Harvard Robotics Laboratory. 1990; 90–7, Technical Report