3D Multi-Object Tracking using Lidar

Introduction to Lidar, Autonomous Driving Public Dataset Types, State of the Art Object Recognition Models for Lidar, and a Kalman Filter-based Tracking Algorithm is explained in this tutorial

Yağmur Çiğdem Aktaş
7 min readJul 28, 2022

Hello everyone! I have completed my master's program after a very busy last 6-months period where I was having my internship and preparing my master's thesis report. Without surprise, my project was about “3D Multi-Object Tracking using Lidar for Autonomous Driving” and as a very beginner in Lidar, Tracking, and Autonomous Driving subjects, I decided to share my notes before I forget the details that I had trouble understanding as a beginner :)

This post will have the following structure to explain my project from top to bottom :

  • Background Information
    1. RGB-D Camera
    2. Point Clouds
    3. Object Tracking Types
  • Object Detection using Lidar
    1. PointNet
    2. VoxelNet
    3. SECOND
    4. PointPillar
    5. Model Selection
  • Kalman Filter-based Tracking Algorithm
    1. Main Types of Tracking Methods
    2. Kalman Filter
    3. Mahalanobis Distance
    4. Greedy Match Algorithm
    5. Optimizations