eWand: A calibration framework for wide baseline frame-based and event-based camera systems

TL;DR

eWand introduces a novel calibration method using blinking LEDs inside spheres, enabling faster and more accurate extrinsic calibration for wide baseline multi-camera systems, including both frame-based and event-based cameras.

Contribution

The paper presents eWand, a new calibration framework that replaces traditional 2D patterns with LED spheres, simplifying and speeding up multi-camera extrinsic calibration.

Findings

Provides high accuracy calibration for diverse camera setups

Reduces calibration time compared to traditional methods

Works effectively with both frame- and event-based cameras

Abstract

Accurate calibration is crucial for using multiple cameras to triangulate the position of objects precisely. However, it is also a time-consuming process that needs to be repeated for every displacement of the cameras. The standard approach is to use a printed pattern with known geometry to estimate the intrinsic and extrinsic parameters of the cameras. The same idea can be applied to event-based cameras, though it requires extra work. By using frame reconstruction from events, a printed pattern can be detected. A blinking pattern can also be displayed on a screen. Then, the pattern can be directly detected from the events. Such calibration methods can provide accurate intrinsic calibration for both frame- and event-based cameras. However, using 2D patterns has several limitations for multi-camera extrinsic calibration, with cameras possessing highly different points of view and a wide baseline. The 2D pattern can only be detected from one direction and needs to be of significant size to compensate for its distance to the camera. This makes the extrinsic calibration time-consuming and cumbersome. To overcome these limitations, we propose eWand, a new method that uses blinking LEDs inside opaque spheres instead of a printed or displayed pattern. Our method provides a faster, easier-to-use extrinsic calibration approach that maintains high accuracy for both event- and frame-based cameras.