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Estimation of absolute distance and height of people based on monocular view and deep neural networks for edge devices operating in the visible and thermal spectra

Gąsienica-Józkowy Jan, Cyganek Bogusław, Knapik Mateusz, Głogowski Szymon, Przebinda Łukasz

Annals of Computer Science and Information Systems

2023

Vol. 35

503--511

Accurate estimation of absolute distance and height of objects in open area conditions is a significant challenge. In this paper, we address these problems and we propose a novel approach that combines classical computer vision algorithms with modern neural network-based solutions. Our method integrates object detection, monocular depth estimation, and homography- based mapping to achieve precise and efficient estimations of absolute height and distance. The solution is implemented on the edge device, which enables real-time data processing using both visual and thermography data sources. Experimental evaluation on a height estimation dataset prepared by us demonstrates an accuracy of 97.06\% and validates the effectiveness of our approach.