|
This article is cited in 1 scientific paper (total in 1 paper)
NUMERICAL METHODS AND DATA ANALYSIS
Feature extraction techniques for LIDAR range profile based object recognition
F. B. Baulin, E. V. Buryi Bauman Moscow State Technical University
Abstract:
The article provides an overview of range profile feature extraction methods used in laser identification, detection and ranging systems. It also outlines feature selection methods and highlights their respective limitations. A novel feature selection method which maximizes Euclidian distances between feature vectors is presented. The article also showcases advantages of the proposed technique by extracting features of basic objects (a sphere, a cone, and a cylinder). This method is shown to be effective when feature vector manifolds are not linearly separable due to the unknown viewing aspect of an object. The technique is also effective when feature vector manifolds overlap due to the different objects having similar range profiles.
Keywords:
lidar, laser sensor, backscattering, range profile, pattern recognition, wavelets, feature extraction, feature selection
Received: 13.03.2021 Accepted: 19.05.2021
Citation:
F. B. Baulin, E. V. Buryi, “Feature extraction techniques for LIDAR range profile based object recognition”, Computer Optics, 45:6 (2021), 934–941
Linking options:
https://www.mathnet.ru/eng/co985 https://www.mathnet.ru/eng/co/v45/i6/p934
|
Statistics & downloads: |
Abstract page: | 12 | Full-text PDF : | 10 |
|