Joint Pedestrian Detection and Risk-level Prediction with Motion-Representation-by-Detection

Hirokatsu Kataoka, Teppei Suzuki, Kodai Nakashima, Yutaka Satoh, Yoshimitsu Aoki

研究成果: Conference contribution

抄録

The paper presents a pedestrian near-miss detector with temporal analysis that provides both pedestrian detection and risk-level predictions which are demonstrated on a self-collected database. Our work makes three primary contributions: (i) The framework of pedestrian near-miss detection is proposed by providing both a pedestrian detection and risk-level assignment. Specifically, we have created a Pedestrian Near-Miss (PNM) dataset that categorizes traffic near-miss incidents based on their risk levels (high-, low-, and no-risk). Unlike existing databases, our dataset also includes manually localized pedestrian labels as well as a large number of incident-related videos. (ii) Single-Shot MultiBox Detector with Motion Representation (SSD-MR) is implemented to effectively extract motion-based features in a detected pedestrian. (iii) Using the self-collected PNM dataset and SSD-MR, our proposed method achieved +19.38% (on risk-level prediction) and +13.00% (on joint pedestrian detection and risk-level prediction) higher scores than that of the baseline SSD and LSTM. Additionally, the running time of our system is over 50 fps on a graphics processing unit (GPU).

本文言語English
ホスト出版物のタイトル2020 IEEE International Conference on Robotics and Automation, ICRA 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1021-1027
ページ数7
ISBN(電子版)9781728173955
DOI
出版ステータスPublished - 2020 5月
外部発表はい
イベント2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
継続期間: 2020 5月 312020 8月 31

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Conference

Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
国/地域France
CityParis
Period20/5/3120/8/31

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

フィンガープリント

「Joint Pedestrian Detection and Risk-level Prediction with Motion-Representation-by-Detection」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル