In this paper, we present the Diver Interest via Pointing (DIP) algorithm, a highly modular method for conveying a diver's area of interest to an autonomous underwater vehicle (AUV) using pointing gestures for underwater human-robot collaborative tasks. DIP uses a single monocular camera and exploits human body pose, even with complete dive gear, to extract underwater human pointing gesture poses and their directions. By extracting 2D scene geometry based on the human body pose and density of salient feature points along the direction of pointing, using a low-level feature detector, the DIP algorithm is able to locate objects of interest as indicated by the diver.
Cite
@article{arxiv.2212.01205,
title = {Diver Interest via Pointing: Human-Directed Object Inspection for AUVs},
author = {Chelsey Edge and Junaed Sattar},
journal= {arXiv preprint arXiv:2212.01205},
year = {2022}
}