Real-time underwater stereofusion
| Autor: | Satja Sivčev, James Riordan, Petar Trslic, Daniel Toal, Gerard Dooly, Matija Rossi |
|---|---|
| Přispěvatelé: | SFI |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
fusion
vision Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION GPU real-time 02 engineering and technology underwater lcsh:Chemical technology Remotely operated underwater vehicle Underwater robotics Biochemistry Article Field (computer science) Analytical Chemistry Depth map 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Computer vision Electrical and Electronic Engineering Underwater Instrumentation Monocular business.industry stereo 020207 software engineering tracking Atomic and Molecular Physics and Optics ROV Robot 020201 artificial intelligence & image processing Artificial intelligence business Stereo camera 3D camera |
| Zdroj: | Sensors Volume 18 Issue 11 Sensors (Basel, Switzerland) Sensors, Vol 18, Iss 11, p 3936 (2018) |
| Popis: | Many current and future applications of underwater robotics require real-time sensing and interpretation of the environment. As the vast majority of robots are equipped with cameras, computer vision is playing an increasingly important role it this field. This paper presents the implementation and experimental results of underwater StereoFusion, an algorithm for real-time 3D dense reconstruction and camera tracking. Unlike KinectFusion on which it is based, StereoFusion relies on a stereo camera as its main sensor. The algorithm uses the depth map obtained from the stereo camera to incrementally build a volumetric 3D model of the environment, while simultaneously using the model for camera tracking. It has been successfully tested both in a lake and in the ocean, using two different state-of-the-art underwater Remotely Operated Vehicles (ROVs). Ongoing work focuses on applying the same algorithm to acoustic sensors, and on the implementation of a vision based monocular system with the same capabilities. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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