Privacy Preserving Partial Localization

We propose a partial localization approach for cloud-based visual localization. By applying geometric lifting to the map we prevent the server from knowing the exact client pose. Still, the client can locally combine multiple partial queries into a full pose.

Privacy Preserving Localization and Mapping from Uncalibrated Cameras

We present privacy preserving localization and mapping without the need for calibrated cameras.

Infrastructure-based Multi-Camera Calibration using Radial Projections

A method for automatic camera rig calibration based on a prebuilt model of the environment.

Privacy Preserving Structure-from-Motion

We present the first full Structure-from-Motion pipeline from privacy preserving line features.

Efficient 2D-3D Matching for Multi-Camera Visual Localization

A novel, dynamic feature matching and pose estimation strategy tailored to multi-camera systems.

Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System

A project to develop visual perception systems for autonomous driving in difficult environments.

Towards Robust Visual Odometry with a Multi-Camera System

Direct VIO for multi-camera systems.