Journals / Electrica / 2004 / Cilt: 4 Sayı: 1

TECHNIQUE OF FUZZY TUNED STOCHASTIC SCANPATHS FOR ROBOT VISION

Journal
Electrica
Pages
1031–1043
Publication Date
2011-12-28
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

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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

ALLEN, M. J., DIMIROVSKI, G. M., GOUGH, N. E., MEHDI, Q. H. (2011). TECHNIQUE OF FUZZY TUNED STOCHASTIC SCANPATHS FOR ROBOT VISION. Electrica, Cilt: 4 Sayı: 1, 1031–1043. https://ajindex.com/articles/1017690

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