Spotting advertisements from above: billboard detection and segmentation in UAV imagery
[ 1 ] Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ 2 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doktorant ze Szkoły Doktorskiej | [ P ] pracownik
[2.2] Automatyka, elektronika, elektrotechnika i technologie kosmiczne
2023
rozdział w monografii naukowej / referat
angielski
- object detection
- segmentation
- deep learning
- YOLO
- UAV
EN In this work, deep-learning methods were researched for billboard detection in urban environments. Billboards are one of the adversarial visual pollutants occurring in cities, causing over-saturation of visual stimulation. Due to this, we develop an algorithm that helps in the analysis and management of urban space. We utilise near real-time object detection methods to detect and segment them on images registered by unmanned aerial vehicles (UAVs). Research is based on recent algorithms from the YOLO family with modified heads for the instance segmentation task. We gathered images and prepared hand-annotated labels for training and evaluation purposes of deep learning approaches. We reached the mAP@0.5 metric of 0.61 for detection and 0.60 for segmentation, enabling us to develop smart city applications.
67 - 72
dla wszystkich w zakresie dozwolonego użytku
otwarte repozytorium
ostateczna wersja opublikowana
w momencie opublikowania
20