夜間における車載カメラを使った歩行者認識のための夜間画像の視認性向上

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2020/05/01

タイトル(英語): Improving the Visibility of Nighttime Images for Pedestrian Recognition using In-Vehicle Camera

著者名: 小倉　亮太（公立はこだて未来大学），長崎　健（公立はこだて未来大学），松原　仁（公立はこだて未来大学）

著者名(英語): Ryota Ogura (Future University Hakodate), Takeshi Nagasaki (Future University Hakodate), Hitoshi Matsubara (Future University Hakodate)

キーワード: 歩行者認識，単眼カメラ，画像変換，深層学習　　pedestrian detection，monocular camera，image convert，DeepLearning

要約(英語): There is a need for methods to recognize night pedestrian to reduce pedestrian traffic accidents at night. In this paper, we proposed the method that converts images using continuous nighttime images from in-vehicle camera. The proposed method performs feature extraction that doesn't depend on own vehicle speed because inputting continuous nighttime images, and the function of convolution layer that performs dimensionality reduction. In order to confirm the effectiveness of the proposed method, we prepared the images of simulation and camera. The nighttime images were conversed with the proposed method. After conversion, we calculated the recognition performance by applying object detection which is an object recognition method. We showed the proposed method is more robust against the own vehicle speed change.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.140 No.5 （2020）

本誌掲載ページ: 531-538 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/140/5/140_531/_article/-char/ja/