Paper
7 June 2023 Event-based YOLO object detection: proof of concept for forward perception system
Waseem Shariff, Muhammad Ali Farooq, Joe Lemley, Peter Corcoran
Author Affiliations +
Proceedings Volume 12701, Fifteenth International Conference on Machine Vision (ICMV 2022); 127010A (2023) https://doi.org/10.1117/12.2679341
Event: Fifteenth International Conference on Machine Vision (ICMV 2022), 2022, Rome, Italy
Abstract
Neuromorphic vision or event vision is an advanced vision technology, where in contrast to visible camera sensors that output pixels, the event vision generates neuromorphic events every time there’s a brightness change which exceeds a specific threshold in the field of view (FoV). This study focuses on leveraging neuromorphic event data for roadside object detection. This is a proof of concept towards building artificial intelligence (AI) based imaging pipelines which can be used for forward perception systems for advanced vehicular applications. The focus is on building efficient stateof- the-art object detection networks with better inference results for fast-moving forward perception using an event camera. In this article, the event simulated A2D2 dataset is manually annotated and trained on two different YOLOv5 networks (small and large variants). To further assess its robustness, single model testing and ensemble model testing are carried out.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Waseem Shariff, Muhammad Ali Farooq, Joe Lemley, and Peter Corcoran "Event-based YOLO object detection: proof of concept for forward perception system", Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 127010A (7 June 2023); https://doi.org/10.1117/12.2679341
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KEYWORDS
Education and training

Object detection

Data modeling

Cameras

Sensors

Machine learning

Performance modeling

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