Authors:
Bence Gálai
1
and
Csaba Benedek
2
Affiliations:
1
Institute for Computer Science and Control, Hungary
;
2
Institute for Computer Science and Control and Péter Pázmány Catholic University, Hungary
Keyword(s):
Gait Recognition, Lidar.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Video Surveillance and Event Detection
Abstract:
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 fiv
e tests scenarios with multiple walking pedestrians, which have been
recorded by both sensors in parallel.
(More)