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Vision Systems with the Human in the Loop
EURASIP Journal on Advances in Signal Processing volume 2005, Article number: 302161 (2005)
The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.
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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Bauckhage, C., Hanheide, M., Wrede, S. et al. Vision Systems with the Human in the Loop. EURASIP J. Adv. Signal Process. 2005, 302161 (2005). https://doi.org/10.1155/ASP.2005.2375
Keywords and phrases
- cognitive vision
- contextual reasoning