Gait Recognition with Compact Lidar Sensors

Bence Gálai, Csaba Benedek


In this paper, we present a comparative study on gait and activity analysis using LiDAR scanners with different resolution. Previous studies showed that gait recognition methods based on the point clouds of a Velodyne HDL-64E Rotating Multi-Beam LiDAR can be used for people re-identification in outdoor surveillance scenarios. However, the high cost and the weight of that sensor means a bottleneck for its wide application in surveillance systems. The contribution of this paper is to show that the proposed Lidar-based Gait Energy Image descriptor can be efficiently adopted to the measurements of the compact and significantly cheaper Velodyne VLP-16 LiDAR scanner, which produces point clouds with a nearly four times lower vertical resolution than HDL-64. On the other hand, due to the sparsity of the data, the VLP-16 sensor proves to be less efficient for the purpose of activity recognition, if the events are mainly characterized by fine hand movements. The evaluation is performed on five tests scenarios with multiple walking pedestrians, which have been recorded by both sensors in parallel.


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Paper Citation

in Harvard Style

Gálai B. and Benedek C. (2017). Gait Recognition with Compact Lidar Sensors . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 426-432. DOI: 10.5220/0006124404260432

in Bibtex Style

author={Bence Gálai and Csaba Benedek},
title={Gait Recognition with Compact Lidar Sensors},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},

in EndNote Style

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - Gait Recognition with Compact Lidar Sensors
SN - 978-989-758-227-1
AU - Gálai B.
AU - Benedek C.
PY - 2017
SP - 426
EP - 432
DO - 10.5220/0006124404260432