  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.
