The goal of this paper is to classify objects mapped by LiDAR sensor into different classes such as vehicles, pedestrians and bikers. Utilizing a LiDAR-based object detector and Neural Networks-based classifier, a novel real-time object detection is presented essentially with respect to aid self-driving vehicles in recognizing and classifying other objects encountered in the course of driving and proceed accordingly. We discuss our work using machine learning methods to tackle a common high-level problem found in machine learning applications for self-driving cars: the classification of pointcloud data obtained from a 3D LiDAR sensor.
@article{arxiv.1906.11899,
title = {Lidar based Detection and Classification of Pedestrians and Vehicles Using Machine Learning Methods},
author = {Farzad Shafiei Dizaji},
journal= {arXiv preprint arXiv:1906.11899},
year = {2019}
}