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IJAT Vol.15 No.6 pp. 794-803
doi: 10.20965/ijat.2021.p0794
(2021)

Paper:

Surrounding Structure Estimation Using Ambient Light

Bilal Ahmed Mir*, Tohru Sasaki**,†, Yusuke Nagahata*, Eri Yamabe*, Naoya Miwa*, and Kenji Terabayashi**

*Graduate School of Science and Engineering for Education, University of Toyama
3190 Gofuku, Toyama, Toyama 930-8555, Japan

**Department of Mechanical and Intellectual Systems Engineering, University of Toyama, Toyama, Japan

Corresponding author

Received:
March 26, 2021
Accepted:
July 7, 2021
Published:
November 5, 2021
Keywords:
image sensing, visual affordance, ambient light, structure estimation
Abstract

Image measurement technology – widely used in present society – has made substantial progress. It involves processes such as image input, target extraction, and measurement of the extracted region to obtain information from an image. These processes are computationally intensive because they require a large amount of information such as complex features, which is often an obstacle to improving and speeding up image processing tasks. In contrasts, living organisms easily recognize their own surroundings in real time. In cognitive science research studies, for example, visual affordance studies have shown that organisms perceive and recognize their surrounding environment and objects from ambient light, which is formed by reflected and scattered light in the environment. By applying this natural mechanism to image measurement technology, it is possible to obtain the information necessary to recognize the surrounding environment by observing ambient light without necessarily detecting or recognizing the object. In this study, we propose a direct method of assessing the surrounding environment by capturing ambient light as luminance.

Cite this article as:
Bilal Ahmed Mir, Tohru Sasaki, Yusuke Nagahata, Eri Yamabe, Naoya Miwa, and Kenji Terabayashi, “Surrounding Structure Estimation Using Ambient Light,” Int. J. Automation Technol., Vol.15, No.6, pp. 794-803, 2021.
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Last updated on Nov. 30, 2021