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- ONO Shintaro
- 東京大学生産技術研究所 次世代モビリティ研究センター
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- KIDA Atsumu
- 東京大学大学院工学系研究科
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- WATANABE Takanoshin
- コンチネンタル・オートモーティブ(株)
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- KARG Michelle
- Continental ADC Automotive Distance Control Systems GmbH
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- SUDA Yoshihiro
- 東京大学生産技術研究所 次世代モビリティ研究センター
Bibliographic Information
- Other Title
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- 自動運転のための警察官の手信号の認識システム
- ジドウ ウンテン ノ タメ ノ ケイサツカン ノ テシンゴウ ノ ニンシキ システム
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Description
<p>We developed a method to recognize such hand signals from on-vehicle camera, based on deep-learning technique. The skeleton coordinate of the performer is input to a deep learning method, to classify the signal state into Red/Green or Red/Green/Other. From the state and the continuation conditions, the instruction Stop/Go is determined. Our preliminary experiment proved that quite similar short actions are included both in Red and Green, and it is better to separate such actions as “Other”. In the final result, Stop/Go can be appropriately determined, and at the same time, the temporal difference of estimation between switching Stop/Go (Too-early Go and Too-late Stop) was less than 0.43 seconds.</p>
Journal
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- SEISAN KENKYU
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SEISAN KENKYU 72 (2), 195-200, 2020-03-01
Institute of Industrial Science The University of Tokyo
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Details 詳細情報について
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- CRID
- 1390565134845101056
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- NII Article ID
- 130007827153
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- NII Book ID
- AN00127075
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- ISSN
- 18812058
- 0037105X
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- NDL BIB ID
- 030416306
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL Search
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed