RESEARCH FOR CORRECTION OF PERSON IDENTIFICATION USING OBJECT TRACKING TECHNOLOGY
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- INOUE Haruka
- 大阪経済大学 情報社会学部
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- UMEHARA Yoshimasa
- 関西大学 先端科学技術推進機構
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- IMAI Ryuichi
- 法政大学 デザイン工学部
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- KAMIYA Daisuke
- 琉球大学 工学部
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- TANAKA Shigenori
- 関西大学 総合情報学部
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- NAKAHATA Koki
- 関西大学大学院 総合情報学研究科
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- SHIMANO Hiroki
- 関西大学大学院 総合情報学研究科
Bibliographic Information
- Other Title
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- オブジェクト追跡技術を用いた人物識別の補正に関する研究
Description
<p> In Japan, taking the opportunity of the proposal of Society 5.0, the introduction of state-of-the-art technologies, such as IoT and AI, has been being examined. In particular, at construction sites, such technologies are expected to greatly contribute to an improvement in the productivity and development of safety management. A development of technology for managing the positions and conditions of workers to decrease accidents of minor collisions or falls has been attracting growing interest. Thus, paying attention to the safety management of construction sites, the authors have proposed the some methods of person identification by deep learning focusing on patterns pasted on the workers’ helmets. In the existing researches, however, there was a problem that the same person was not correctly identified successively between frames when erroneous identification occurs due to the difference in the distance from the camera or the way the pattern was reflected. In this research, a new correction method is devised based on tracking of the helmets and improved the person identification method. As a result of conducting demonstration experiments, knowledge was obtained that this correction method is effective.</p>
Journal
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- Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics)
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Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 78 (2), I_122-I_130, 2022
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1390854717652244096
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- ISSN
- 21856591
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
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- Abstract License Flag
- Disallowed