Diver Interest via Pointing: Human-Directed Object Inspection for AUVs
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Dec 2022.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 2.
4 papers.
- 2026GesVLA: Gesture-Aware Vision-Language-Action Model Embedded Representationscited by 2
- 2026GIVE: Grounding Human Gestures in Vision-Language-Action Modelscited by 1
- 2024A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object trackingcited by 0
- 2025SafeDiver: Cooperative AUV-USV Assisted Diver Communication via Multi-agent Reinforcement Learning Approachcited by 0
- 2026GIVE: Grounding Human Gestures in Vision-Language-Action Models11 Jun 2026
- 2026GesVLA: Gesture-Aware Vision-Language-Action Model Embedded Representations21 May 2026
- 2025SafeDiver: Cooperative AUV-USV Assisted Diver Communication via Multi-agent Reinforcement Learning Approach15 Sep 2025
- 2024A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object tracking29 Jan 2024