TY - GEN
T1 - Pedestrian flow estimation using sparse observation for autonomous vehicles
AU - Neto, Ranulfo P.Bezerra
AU - Ohno, Kazunori
AU - Westfechtel, Thomas
AU - Tadokoro, Satoshi
N1 - Funding Information:
This work was supported by JST CREST Recognition, Summarization and Retrieval of Large-Scale Multimedia Data Grant Number JP14532298, Japan. REFERENCES
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - One of the major challenges that autonomous cars are facing today is the unpredictability of pedestrian movement in urban environments. Since pedestrian data acquired by vehicles are sparse observed a pedestrian flow directed graph is proposed to understand pedestrian behavior. In this work, an autonomous electric vehicle is employed to gather LiDAR and camera data. Pedestrian tracking information and semantic information from the environment are used with a probabilistic approach to create the graph. In order to refine the graph a set of outlier removal techniques are described. The graph-based pedestrian flow shows an increase of 61.29 % of coverage zone, and the outlier removal approach successfully removed 81 % of the edges.
AB - One of the major challenges that autonomous cars are facing today is the unpredictability of pedestrian movement in urban environments. Since pedestrian data acquired by vehicles are sparse observed a pedestrian flow directed graph is proposed to understand pedestrian behavior. In this work, an autonomous electric vehicle is employed to gather LiDAR and camera data. Pedestrian tracking information and semantic information from the environment are used with a probabilistic approach to create the graph. In order to refine the graph a set of outlier removal techniques are described. The graph-based pedestrian flow shows an increase of 61.29 % of coverage zone, and the outlier removal approach successfully removed 81 % of the edges.
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U2 - 10.1109/ICAR46387.2019.8981587
DO - 10.1109/ICAR46387.2019.8981587
M3 - Conference contribution
AN - SCOPUS:85084284899
T3 - 2019 19th International Conference on Advanced Robotics, ICAR 2019
SP - 779
EP - 784
BT - 2019 19th International Conference on Advanced Robotics, ICAR 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th International Conference on Advanced Robotics, ICAR 2019
Y2 - 2 December 2019 through 6 December 2019
ER -