Data-Driven Worker Detection from Load-View Crane Camera
Tanittha Sutjaritvorakul, Axel Vierling, Karsten Berns
Abstract
Data-Driven Worker Detection from Load-View Crane Camera Tanittha Sutjaritvorakul, Axel Vierling and Karsten Berns Pages 864-871 (2020 Proceedings of the 37th ISARC, Kitakyushu, Japan, ISBN 978-952-94-3634-7) Abstract: Cranes as an essential part of the construction machinery, are one of the prominent sources of fatalities in the construction sites. The camera assistant system can contribute significantly to the safety of the crane operation particularly in blind lifts tasks, where the operator highly relies on the load-view camera. In this paper, we address the worker detection from an off-the-shelf load-view crane camera using a data-driven approach. Due to the difficulties in collecting data, we generate five training datasets via a simulation platform to build up the synthetic samples to improve the state-of-the-art detector. Despite the fact that only the simulation data is used as training datasets, the trained network demonstrates the average precision of up to 66.84% in two real-world scenarios. Keywords: Construction safety; Crane simulation; Worker detection; Visibility assistance DOI: https://doi.org/10.22260/ISARC2020/0119 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley