Supporting Detection of Near and Far Pedestrians in a Collision Prediction System

Lucas F. S. Cambuim, Edna Barros

2021

Abstract

This paper proposes a multi-window-based detector to locate pedestrians near and distant. This detector is introduced in a pedestrian collision prediction (PCP) system. We developed an evaluation strategy for the proposed PCP system based on a synthetic collision database, which allowed us to analyze collision prediction quality improvements. Results demonstrate that the combination of different window subdetectors outperforms individual subdetectors’ accuracy and YOLO-based detector. Once our system achieved a processing rate of 30 FPS when processing images in HD resolution, results demonstrated an increase in the number of scenarios that the system could entirely avoid a collision compared to a YOLO-based system.

Paper Citation

in Harvard Style

Cambuim L. and Barros E. (2021). Supporting Detection of Near and Far Pedestrians in a Collision Prediction System. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 669-676. DOI: 10.5220/0010253706690676

in Bibtex Style

@conference{visapp21,
author={Lucas F. S. Cambuim and Edna Barros},
title={Supporting Detection of Near and Far Pedestrians in a Collision Prediction System},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={669-676},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010253706690676},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Supporting Detection of Near and Far Pedestrians in a Collision Prediction System
SN - 978-989-758-488-6
AU - Cambuim L.
AU - Barros E.
PY - 2021
SP - 669
EP - 676
DO - 10.5220/0010253706690676
PB - SciTePress