Traffic sign detection and recognition using event camera image reconstruction

Kamil Jeziorek; Tomasz Kryjak

Traffic sign detection and recognition using event camera image reconstruction

Computer Vision and Pattern Recognition 2022-12-19 v1 Image and Video Processing

Authors: Kamil Jeziorek , Tomasz Kryjak

Abstract

This paper presents a method for detection and recognition of traffic signs based on information extracted from an event camera. The solution used a FireNet deep convolutional neural network to reconstruct events into greyscale frames. Two YOLOv4 network models were trained, one based on greyscale images and the other on colour images. The best result was achieved for the model trained on the basis of greyscale images, achieving an efficiency of 87.03%.

Keywords

object detection image classification

Cite

@article{arxiv.2212.08387,
  title  = {Traffic sign detection and recognition using event camera image reconstruction},
  author = {Kamil Jeziorek and Tomasz Kryjak},
  journal= {arXiv preprint arXiv:2212.08387},
  year   = {2022}
}

Comments

Paper accepted for publication in: Zeszyty Studenckiego Towarzystwa Naukowego, 59. Hutnicza Konferencja Studenckich Kol Naukowych AGH,ISSN 1732-0925, 2022 nr 38, pp. 127-134. (original manuscript in Polish)

Traffic sign detection and recognition using event camera image reconstruction

Abstract

Keywords

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