Open Access
28 November 2017 Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion
Seong Kyung Kwon, Eugin Hyun, Jin-Hee Lee, Jonghun Lee, Sang Hyuk Son
Author Affiliations +
Abstract
Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar–radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Seong Kyung Kwon, Eugin Hyun, Jin-Hee Lee, Jonghun Lee, and Sang Hyuk Son "Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion," Optical Engineering 56(11), 113112 (28 November 2017). https://doi.org/10.1117/1.OE.56.11.113112
Received: 1 June 2017; Accepted: 6 November 2017; Published: 28 November 2017
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CITATIONS
Cited by 17 scholarly publications.
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KEYWORDS
Radar

LIDAR

Sensor fusion

Doppler effect

Environmental sensing

Sensors

Cameras

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