OMNIDIRECTIONAL CAMERA-BASED TRAFFIC LIGHT DETECTION USING DEEP LEARNING APPROACH
- 提供方法
- 本サイト上にてダウンロード・閲覧可
- 形態
- 価格
- 一般価格(税込):¥1,100 会員価格(税込):¥880
- 文献番号
- 20219003
- 文献・情報種別
- その他の国際会議
- 掲載ページ
- 1-3(Total 3 p)
- 発行年月
- 2021年 9月
- 出版社
- (公社)自動車技術会
- 言語
- 英語
書誌事項
著者(英) | 1) Yasuyuki Ishida, 2) Toshio Ito |
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勤務先(英) | 1) Shibaura Institute of Technology, 2) Shibaura Institute of Technology |
抄録(英) | In recent years, there has been a growing need for automated driving due to issues such as urbanization and aging populations. Autonomous mobility needs to cross the road safely, and one of the most important objects is the traffic light. Therefore, we detect traffic lights, including their color information. It is suitable for automated vehicles since the omnidirectional camera has a wide field of view. However, the omnidirectional image is different from an ordinal rectangle image, that the objects are arranged in a circle and the spatial resolution in the radial direction is non-constant. Thus, object detection requires different feature information rather than ordinally rectangular images. We divide the omnidirectional image into four parts so that the rotations are in the same direction. Then, we encoded the divided images and input them into the neural network to improve the accuracy. 翻訳 |