Recognition of Pedestrian Traffic Light at Crosswalk for a Mobile Robot Using Deep Learning
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- SHIGEMATSU Kosuke
- Graduate School of Systems and Information Engineering, University of Tsukuba
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- KONISHI Yuichi
- Graduate School of Systems and Information Engineering, University of Tsukuba
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- MITSUDOME Ryosuke
- Graduate School of Systems and Information Engineering, University of Tsukuba
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- TSUBOUCHI Takashi
- Faculty of Engineering, Information and System, University of Tsukuba
Bibliographic Information
- Other Title
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- ロボットの横断歩道横断のための深層学習を用いた歩行者用信号機の認識
- ロボット ノ オウダン ホドウ オウダン ノ タメ ノ シンソウ ガクシュウ オ モチイタ ホコウシャヨウ シンゴウキ ノ ニンシキ
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Description
<p>This paper describes recognition of pedestrian traffic light at crosswalk for a mobile robot using deep learning. In order for a robot to cross a crosswalk, the robot needs to recognize the color of the traffic light like a human. A recognition of traffic light by camera images based on manually designed image features is possible. However, it requires significant amount of labor to adjust parameters under changing lighting condition. Therefore, in this paper we tried to recognize traffic lights using deep learning. The proposed method consists of two processes: a detection of traffic light and a classification of a traffic light color using deep learning. These processes can be processed in an allowable time by a small computer mountable on a mobile robot. Through a series of experiments, the proposed method successfully recognizes traffic signal in real environments.</p>
Journal
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- Transactions of the Society of Instrument and Control Engineers
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Transactions of the Society of Instrument and Control Engineers 54 (1), 99-110, 2018
The Society of Instrument and Control Engineers
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Details 詳細情報について
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- CRID
- 1390001204507873536
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- NII Article ID
- 130006319127
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- NII Book ID
- AN00072392
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- ISSN
- 18838189
- 04534654
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- NDL BIB ID
- 028794872
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL Search
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed