RT Conference Proceedings
T1 Parallel proccessing applied to object detection with a Jetson TX2 embedded system.
A1 Benito-Picazo, Jesús
A1 Fernández-Rodríguez, Jose David
A1 Domínguez-Merino, Enrique
A1 Palomo-Ferrer, Esteban José
A1 López-Rubio, Ezequiel
K1 Aprendizaje automático (Inteligencia artificial)
K1 Teledetección
K1 Procesado de imágenes
AB Video streams from panoramic cameras represent a powerful tool for automated surveillance systems, but naïve implementations typically require very intensive computational loads for applying deep learning models for automated detection and tracking of objects of interest, since these models require relatively high resolution to reliably perform object detection. In this paper, we report a host of improvements to our previous state-of-the-art software system to reliably detect and track objects in video streams from panoramic cameras, resulting in an increase in the processing framerate in a Jetson TX2 board, with respect to our previous results. Depending on the number of processes and the load profile, we observe up to a five-fold increase in the framerate.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/27439
UL https://hdl.handle.net/10630/27439
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 mar 2026