Self Calibration of a Sonar-Vision System for Underwater Vehicles: A New Method and a Dataset

水下航行器声呐视觉系统的自校准:一种新方法和数据集

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Abstract

Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar-vision system. This method is based on motion comparisons between both images and allows us to compute the transformation matrix between the camera and the sonar and to estimate the camera's focal length. The main advantage of our method lies in performing the calibration without any specific calibration pattern, while most other existing methods use physical targets. In this paper, we also propose a new sonar-vision dataset and use it to prove the validity of our calibration method.

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