Event-based, 6-DOF Camera Tracking from Photometric Depth Maps

TL;DR

This paper introduces a method for real-time, low-latency 6-DOF camera tracking using event cameras and photometric depth maps, enabling reliable tracking in high-speed and high-dynamic-range scenes.

Contribution

The paper presents a novel approach for event camera pose estimation from photometric depth maps, achieving low-latency tracking suitable for high-speed scenes.

Findings

Effective in high-speed indoor and outdoor scenes

Works with scenes of high dynamic range

Eliminates latency in camera tracking

Abstract

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide reliable visual information during high-speed motions or in scenes characterized by high dynamic range. These features, along with a very low power consumption, make event cameras an ideal complement to standard cameras for VR/AR and video game applications. With these applications in mind, this paper tackles the problem of accurate, low-latency tracking of an event camera from an existing photometric depth map (i.e., intensity plus depth information) built via classic dense reconstruction pipelines. Our approach tracks the 6-DOF pose of the event camera upon the arrival of each event, thus virtually eliminating latency. We successfully evaluate the method in both indoor and outdoor scenes and show that---because of the technological advantages of the event camera---our pipeline works in scenes characterized by high-speed motion, which are still unaccessible to standard cameras.