This work addresses an automated system that supports the "Maintenance on Condition"paradigm. The system automatically processes auto-recorded video streams collected by a wayside camera capture device, and proceeds to a preliminary analysis in search for posture errors.We present and discuss a novel system that provides a proper identification of pantograph heads from video sources or image sequences and proceeds to recover the 3D asset from a single 2D image. The system exploits modern Deep Learning (DL) networks to extract a preliminary pantograph shape from the video sequence, then applies an optimization algorithm to estimate accurate position and orientation.A comparative and exhaustive analysis with few hundreds of samples shows the accuracy of the algorithm and the robustness to changes in illumination and other environmental conditions.
|Titolo:||Accurate Identification of 3D Pose through Reprojection onto a Single Image from Mask-RCNN Contour|
BARIS, Gabriele (Corresponding)
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||4.1 Contributo Atti Congressi/Articoli in extenso|