Globally-Optimal Contrast Maximisation for Event Cameras

Abstract

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an event camera operate independently and asynchronously. They measure changes of the logarithmic brightness and return them in the highly discretised form of time-stamped events indicating a relative change of a certain quantity since the last event. New models and algorithms are needed to process this kind of measurements. The present work looks at several motion estimation problems with event cameras. The flow of the events is modelled by a general homographic warping in a space-time volume, and the objective is formulated as a maximisation of contrast within the image of warped events. Our core contribution consists of deriving globally optimal solutions to these generally non-convex problems, which removes the dependency on a good initial guess plaguing existing methods. Our methods rely on branch-and-bound optimisation and employ novel and efficient, recursive upper and lower bounds derived for six different contrast estimation functions. The practical validity of our approach is demonstrated by a successful application to three different event camera motion estimation problems.

arXiv admin note: substantial text overlap with arXiv:2203.03914

References in corpus (2)

• Globally-Optimal Event Camera Motion Estimation
• Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles

Cited by in corpus (14)

• Secrets of Event-Based Optical Flow
• CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization
• The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data
• Event-based Background-Oriented Schlieren
• Event Collapse in Contrast Maximization Frameworks
• Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical Flow
• LECalib: Line-Based Event Camera Calibration
• A 5-Point Minimal Solver for Event Camera Relative Motion Estimation
• An N-Point Linear Solver for Line and Motion Estimation with Event Cameras
• Accelerating Globally Optimal Consensus Maximization in Geometric Vision
• Continuous Event-Line Constraint for Closed-Form Velocity Initialization
• Event-based Photometric Bundle Adjustment
• Event-based Mosaicing Bundle Adjustment
• Dynamic Event Camera Calibration