TY - GEN
T1 - SVM based Pedestrian Detection System for Sidewalk Snow Removing Machines
AU - Sasaki, Yuta
AU - Emaru, Takanori
AU - Ravankar, Ankit A.
N1 - Funding Information:
*This work was partially supported by JSPS Grant-in-Aid for Scientific Research (KAKEn Hi) Project JP20K04392 and Sapporo city project “Alternative techniques for traffic guides in sidewalk snow removal”. 1Yuta Sasaki is with Graduate School of Engineering, Division of Human Mechanical Systems & Design, Hokkaido University, Sapporo, 060-8628, Japan. y u 0 0 d - i r i s @ e i s . h o k u d a i . a c . j p 2Takanori Emaru and Ankit A. Ravankar are with Faculty of Engineering, Division of Human Mechanical Systems & Design, Hokkaido University, Sapporo, 060-8628, Japan. {emaru,ankit}@eng.hokudai.ac.jp *Corresponding Author: Y. Sasaki and AA. Ravankar
Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/11
Y1 - 2021/1/11
N2 - In this paper, we present a novel pedestrian detection system for sidewalk snow removing vehicles particularly for night driving scenarios. The information in front of the snowplow is obtained by clustering and classifying objects using LiDAR point clouds. A robust pedestrian detection and classification algorithm using the support vector machine(SVM) is proposed. We tested the system on an actual machine and the accuracy our method is verified by experiments.
AB - In this paper, we present a novel pedestrian detection system for sidewalk snow removing vehicles particularly for night driving scenarios. The information in front of the snowplow is obtained by clustering and classifying objects using LiDAR point clouds. A robust pedestrian detection and classification algorithm using the support vector machine(SVM) is proposed. We tested the system on an actual machine and the accuracy our method is verified by experiments.
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U2 - 10.1109/IEEECONF49454.2021.9382618
DO - 10.1109/IEEECONF49454.2021.9382618
M3 - Conference contribution
AN - SCOPUS:85103740418
T3 - 2021 IEEE/SICE International Symposium on System Integration, SII 2021
SP - 700
EP - 701
BT - 2021 IEEE/SICE International Symposium on System Integration, SII 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE/SICE International Symposium on System Integration, SII 2021
Y2 - 11 January 2021 through 14 January 2021
ER -