Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2004 / Cilt: 4 - Sayı: 1

Technique of fuzzy tuned stochastic scanpaths for robot vision

Pages
1031–1043
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show how the technique can reliably locate objects in scene whilst examining only a fraction of the image surface, e.g. 5%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The real-time processing of frame sequences obtained from cameras mounted on autonomous mobile robots and vehicles is a computationally intensive task.
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Key Findings & Data:The results show how the technique can reliably locate objects in scene whilst examining only a fraction of the image surface, e.g. 5%.
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Conclusion & Impact:The paper concludes with a discussion on research insofar accomplished and proposes ideas for future work.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The real-time processing of frame sequences obtained from cameras mounted on autonomous mobile robots and vehicles is a computationally intensive task. This paper is a review of the work carried out so far in the development of a procedure using fuzzy-tuned stochastic 'scanpaths' for efficiently scanning images in a frame sequence. A concise explanation of using fuzzy-tuned stochastic scanpaths is given here followed by a summary of the experimental work that has been undertaken to date and results achieved. The results show how the technique can reliably locate objects in scene whilst examining only a fraction of the image surface, e.g. 5%. The paper concludes with a discussion on research insofar accomplished and proposes ideas for future work.

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Cite This Article

MEHDI, Q. H., DIMIROVSKI, G. M., ALLEN, M. J., GOUGH, N. E. (2022). Technique of fuzzy tuned stochastic scanpaths for robot vision. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 4 - Sayı: 1, 1031–1043. https://ajindex.com/articles/543861

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References (10)

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