Focusing an event-based camera: towards spatiotemporal characterization of neuromorphic vision systems

Stephen D. Burks; Jonah P. Sengupta; David P. Haefner; David Lee

doi:10.1117/12.3013108

7 June 2024 Focusing an event-based camera: towards spatiotemporal characterization of neuromorphic vision systems

Stephen D. Burks, Jonah P. Sengupta, David P. Haefner, David Lee

Proceedings Volume 13045, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXV; 130450O (2024) https://doi.org/10.1117/12.3013108
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Neuromorphic sensors (also known as event based cameras) behave differently than traditional imaging sensors as they respond only to changes in stimuli as they occur. They typically have higher dynamic range and frame rates than traditional imaging systems while using less power than other imaging systems because a pixel only outputs data when a stimulus occurs at that pixel. There are a variety of uses for neuromorphic sensors from temporal anomaly detection to autonomous driving. While the information in the output of the neuromorphic sensor correlates to a change in stimuli, there has not been a defined means to characterize neuromorphic sensors in order to predict performance from a given stimuli. This study focuses on the measurement of the temporal and spatial response of a neuromorphic sensor with additional discussion on model performance based upon these measurements.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Stephen D. Burks, Jonah P. Sengupta, David P. Haefner, and David Lee "Focusing an event-based camera: towards spatiotemporal characterization of neuromorphic vision systems", Proc. SPIE 13045, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXV, 130450O (7 June 2024); https://doi.org/10.1117/12.3013108

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