The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Purposive and qualitative active vision
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.>
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A computer algorithm for reconstructing a scene from two projections
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The Interpretation of Visual Motion
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Computational vision and regularization theory
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Cited by
Recognizing human action in time-sequential images using hidden Markov model
Yamato, J., Ohya, J., & Ishii, K. (2003) · Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1992.223161 · Cited by 1,273
The objects of action and perception
Goodale, M. A., & Keith Humphrey, G. (1998) · Cognition · doi:10.1016/s0010-0277(98)00017-1 · Cited by 438
Bajcsy, R., Aloimonos, Y., & Tsotsos, J. K. (2018) · Autonomous Robots · doi:10.1007/s10514-017-9615-3 · Cited by 328
An automatic assessment scheme for steel quality inspection
Wiltschi, K., Pinz, A., & Lindeberg, T. (2000) · Machine Vision and Applications · doi:10.1007/s001380050130 · Cited by 89
FLAR: A Unified Prototype Framework for Few-sample Lifelong Active Recognition
Fan, L., Xiong, P., Wei, W., & Wu, Y. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01511 · Cited by 6
Metadata
- Authors
- Aloimonos, J.
- Venue
- [1990] Proceedings. 10th International Conference on Pattern Recognition
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-04
- Volume
- i
- Pages
- 346-360
- ISSN
- 1041-3278 (ISSN-L)
- OpenAlex
- W1622015710
- Cited by
- 291
- References
- 25
- FWCI
- 17.70
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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