Diver Interest via Pointing: Human-Directed Object Inspection for AUVs
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Dec-2-2022
- Country:
- North America
- United States
- Oregon (0.04)
- New York
- Richmond County > New York City (0.04)
- Queens County > New York City (0.04)
- New York County > New York City (0.04)
- Kings County > New York City (0.04)
- Bronx County > New York City (0.04)
- Nevada > Clark County
- Las Vegas (0.04)
- Minnesota > Hennepin County
- Minneapolis (0.14)
- Canada > Quebec
- Montreal (0.04)
- United States
- Asia
- Malaysia > Kuala Lumpur
- Kuala Lumpur (0.04)
- Japan > Honshū
- Kansai > Hyogo Prefecture > Kobe (0.04)
- Malaysia > Kuala Lumpur
- North America
- Genre:
- Research Report (1.00)
- Industry:
- Health & Medicine (0.87)
- Technology:
- Information Technology > Artificial Intelligence
- Vision (1.00)
- Robots (1.00)
- Machine Learning
- Pattern Recognition (0.46)
- Neural Networks > Deep Learning (0.46)
- Information Technology > Artificial Intelligence