Diver Interest via Pointing: Human-Directed Object Inspection for AUVs

TL;DR

The paper introduces the DIP algorithm, enabling AUVs to interpret diver pointing gestures using monocular cameras for improved underwater human-robot collaboration.

Contribution

It presents a modular method that uses human body pose and scene geometry to accurately locate objects of interest indicated by divers.

Findings

Effective detection of diver pointing gestures underwater

Accurate localization of objects of interest based on gestures

Utilizes monocular camera with low-level feature detection

Abstract

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.