Current issues in computer vision

The goal of computer vision is to derive descriptive information about a scene by computer analysis of images of the scene. Vision algorithms can often serve as computational models for biological visual processes, and they also have many practical uses; but this paper treats computer vision as a subject in its own right. Vision problems are often ill-defined, ill-posed, or computationally intractable; nevertheless, successes have been achieved in many specific areas — document processing and industrial inspection, for example. We suggest that by limiting the domain of application, carefully choosing the task, using redundant data (multi-sensor, multi-frame), and applying adequate computing power, useful solutions to many vision problems can be obtained. Methods of designing such solutions are the subject of the emerging discipline ofvision engineering. With projected advances in sensor and computing technologies, the domains of applicability and ranges of problems that can be solved will gradually expand.

[1]  V. K. Prasanna Kumar,et al.  Parallel architectures and algorithms for image understanding , 1991 .

[2]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[3]  J. Schick,et al.  Simultaneous estimation of 3D shape and motion of objects by computer vision , 1991, Proceedings of the IEEE Workshop on Visual Motion.

[4]  Takeo Kanade,et al.  A multiple-baseline stereo , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  P. Dupuis,et al.  Direct method for reconstructing shape from shading , 1991, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  J. Brant Arseneau,et al.  VLSI and neural systems , 1990 .

[7]  Rama Chellappa,et al.  Estimation of Illuminant Direction, Albedo, and Shape from Shading , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

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

[9]  Jake K. Aggarwal,et al.  Integrated Analysis of Thermal and Visual Images for Scene Interpretation , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Paul Dupuis,et al.  Direct method for reconstructing shape from shading , 1991, Optics & Photonics.

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

[12]  Tomaso Poggio,et al.  Computational vision and regularization theory , 1985, Nature.

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

[14]  John Y. Aloimonos,et al.  Unification and integration of visual modules: an extension of the Marr Paradigm , 1989 .

[15]  R L Wildey,et al.  Topography from Single Radar Images , 1984, Science.