Purposive and qualitative active vision
- 4 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. i, 346-360
- https://doi.org/10.1109/icpr.1990.118128
Abstract
The traditional view of the problem of computer vision as a recovery problem is questioned, and the paradigm of purposive-qualitative vision is offered as an alternative. This paradigm considers vision as a general recognition problem (recognition of objects, patterns or situations). To demonstrate the usefulness of the framework, the design of the Medusa of CVL is described. It is noted that this machine can perform complex visual tasks without reconstructing the world. If it is provided with intentions, knowledge of the environment, and planning capabilities, it can perform highly sophisticated navigational tasks. It is explained why the traditional structure from motion problem cannot be solved in some cases and why there is reason to be pessimistic about the optimal performance of a structure from motion module. New directions for future research on this problem in the recovery paradigm, e.g., research on stability or robustness, are suggested.Keywords
This publication has 17 references indexed in Scilit:
- Animate visionArtificial Intelligence, 1991
- A new technique for fully autonomous and efficient 3D robotics hand/eye calibrationIEEE Transactions on Robotics and Automation, 1989
- Learning early-vision computationsJournal of the Optical Society of America A, 1989
- Active visionInternational Journal of Computer Vision, 1988
- Computational vision and regularization theoryNature, 1985
- Four frames suffice: A provisional model of vision and spaceBehavioral and Brain Sciences, 1985
- Computational Approaches to Image UnderstandingACM Computing Surveys, 1982
- A computer algorithm for reconstructing a scene from two projectionsNature, 1981
- Lightness and Retinex TheoryJournal of the Optical Society of America, 1971
- Visual Pattern DiscriminationIEEE Transactions on Information Theory, 1962