LuvHarris: A Practical Corner Detector for Event-cameras

TL;DR

LuvHarris is a real-time, robust corner detection method for event cameras that improves accuracy and speed over existing techniques by introducing a novel event-surface and optimized Harris algorithm implementation.

Contribution

The paper introduces a new corner detection method for event cameras that enhances accuracy and throughput by novel surface design and efficient Harris algorithm implementation.

Findings

Runs 2.6x faster than current state-of-the-art methods

Achieves high accuracy in corner detection

Operates effectively in real-time with high-resolution event cameras

Abstract

There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible. Current state-of-the-art have either unsatisfactory accuracy or real-time performance when considered for practical use, for example when a camera is randomly moved in an unconstrained environment. In this paper, we present yet another method to perform corner detection, dubbed look-up event-Harris (luvHarris), that employs the Harris algorithm for high accuracy but manages an improved event throughput. Our method has two major contributions, 1. a novel "threshold ordinal event-surface" that removes certain tuning parameters and is well suited for Harris operations, and 2. an implementation of the Harris algorithm such that the computational load per event is minimised and computational heavy convolutions are performed only "as-fast-as-possible", i.e. only as computational resources are available. The result is a practical, real-time, and robust corner detector that runs more than 2.6x the speed of current state-of-the-art; a necessity when using high-resolution event-camera in real-time. We explain the considerations taken for the approach, compare the algorithm to current state-of-the-art in terms of computational performance and detection accuracy, and discuss the validity of the proposed approach for event cameras.