Detection of Binary Square Fiducial Markers Using an Event Camera

TL;DR

This paper introduces a real-time method for detecting and decoding binary square fiducial markers directly from event camera data, outperforming RGB-based detectors and operating efficiently on a single CPU thread.

Contribution

The paper presents the first real-time approach for detecting square binary markers using only an event camera and CPU, with superior performance over RGB detectors.

Findings

Achieves real-time detection on a single CPU thread.

Outperforms RGB ArUco marker detector in accuracy.

Operates solely with event camera data without additional sensors.

Abstract

Event cameras are a new type of image sensors that output changes in light intensity (events) instead of absolute intensity values. They have a very high temporal resolution and a high dynamic range. In this paper, we propose a method to detect and decode binary square markers using an event camera. We detect the edges of the markers by detecting line segments in an image created from events in the current packet. The line segments are combined to form marker candidates. The bit value of marker cells is decoded using the events on their borders. To the best of our knowledge, no other approach exists for detecting square binary markers directly from an event camera using only the CPU unit in real-time. Experimental results show that the performance of our proposal is much superior to the one from the RGB ArUco marker detector. The proposed method can achieve the real-time performance on a single CPU thread.