Master Thesis

Fusion of GPS and Visual SLAM
to improve Localization of autonomous vehicles
in urban environments.

by Adam Kalisz

Online Documentation:


  • Introduction
  • What is GPS and VSLAM?
  • Approaches, State of the art
  • Demo: First Tests
  • Conclusion


  • Adam Kalisz
  • Born and raised in Nuremberg
  • A/V Media Designer (aka cameraman)
  • Started 3D Graphics with Cinema 4D R6 CE (2001)
  • Media Engineering (Bachelor)
  • Computer Science (Master)
  • Blender Foundation Certified Trainer
  • Assistant professor for CG at the NIT (Ohm)

Global Positioning System (GPS)

Latitude: 49.414465299999996
Longitude: 11.1300984

This is a location in Langwasser, Nuremberg, Bavaria.

How to use in global map? WGS84, UTM31N, ...?!

Visual Simultaneous Localization And Mapping (VSLAM)

Vision-based approach to determine own pose
and to understand scene

Monocular vs. Stereo

Similar to Structure-from-Motion (SfM)


ElasticFusion: Dense SLAM Without A Pose Graph

Mathematical concepts:

Feature Detection and Description

Feature Matching

Epipolar Geometry

Camera Calibration

Depth Estimation

Point Cloud

Bundle Adjustment

Scan Matching




Somewhat exotic:


First Test:

  • Mounted GoPro Hero 4 Black on Car
  • HTML5 Sensor Recorder
  • HTML5 GPS Track
  • Visual SfM for 3D Reconstruction


  • GPS signal too noisy, unusable
  • What to do with missing GPS data
  • Time consuming sparse reconstruction (700 images, 2 nights)

Thank you!