Computational modelling of visual attention¶
Itti, L., & Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience, 2(3), 194-203.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Attention
- The transfer mechanism — that salience weighting, interrupt protocols, curated feeds, and attention metrics are mathematically equivalent across cognitive, organizational, and computational substrates — was made explicit in Itti and Koch's (2001) computational saliency-map framework, which mechanizes the bottom-up control of attentional deployment in a form portable across substrates.
This sourceCanonical saliency-map framework formalizing bottom-up attentional deployment as a substrate-portable computation
- The transfer mechanism — that salience weighting, interrupt protocols, curated feeds, and attention metrics are mathematically equivalent across cognitive, organizational, and computational substrates — was made explicit in Itti and Koch's (2001) computational saliency-map framework, which mechanizes the bottom-up control of attentional deployment in a form portable across substrates.
- Salience
- In vision and perception, visual saliency maps predict where eyes fixate from feature-contrast across color, orientation, motion, and luminance.
This sourceReviews bottom-up visual saliency maps predicting fixations from feature-contrast across color, orientation, motion, and luminance.
- In vision and perception, visual saliency maps predict where eyes fixate from feature-contrast across color, orientation, motion, and luminance.
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