RT Conference Proceedings
T1 Detección de participantes del tráfico en entornos urbanos sobre imágenes RGB y nubes de puntos 3D.
A1 Montenegro, Jorge
A1 García-Guillén, Alejandro
A1 Castro Payán, Francisco Manuel
A1 Martínez-Rodríguez, Jorge Luis
A1 Morales-Rodríguez, Jesús
K1 Vehículos autodirigidos
K1 Detectores
K1 Redes neuronales (Informática)
K1 Tráfico - Regulación - Métodos de simulación
AB This article proposes the development of a test environment for the detection of traffic participants in urban environments using neural networks based on the processing of data from vehicle sensors: an RGB camera and a 3D LiDAR sensor. It presents the integration of the realistic simulator CARLA (Car Learning to Act), which allows the detailed recreation of complex urban scenarios, together with ROS2 (Robot Operating System), which is a framework for the development of robotic applications. Specifically, for the case of RGB images, the performance of the CNN (Convolutional Neural Network) YOLOv8 and the DETR (Detection Transformer) is qualitatively evaluated. Similarly, for the detection of traffic participants in point clouds, the PV- RCNN (PointVoxel Regional based Convolutional Neural Network) and its evolution Part-A2-Net are analysed.
PB Comité Español de Automática
YR 2024
FD 2024
LK https://hdl.handle.net/10630/33043
UL https://hdl.handle.net/10630/33043
LA spa
NO Montenegro, J., Garc´ıa-Guillen, ´ A., Castro, F.M., Mart´ınez, J.L., Morales, J. 2024. Detection of Traffic Participants in Urban Environments from RGB images and 3D point clouds Jornadas de Autom´atica, 45. https://doi.org/10.17979/ja-cea.2024.45.10870
NO Proyecto de Investigación de Excelencia de la Junta de Andalucía PREMOVE (ProyExcel 00684).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026