研究目的
To present and use an automatic scale accuracy estimation framework, applicable to models reconstructed from optical imagery and associated navigation data, and to evaluate various reconstruction strategies often used in research and industrial ROV deep sea surveys.
研究成果
The study demonstrates the effectiveness of an automatic scale accuracy estimation framework for underwater 3D models, highlighting the importance of navigation fusion strategies in minimizing scale drift and deformation. The most appropriate strategy produced models with errors around 1% in central parts and less than 5% on extremities. The research underscores the significance of collecting evaluation data at various locations and times during surveys to ensure model accuracy.
研究不足
The study is limited by the challenges of underwater image acquisition, including light attenuation and scattering, and the need for additional information to disambiguate scale in monocular camera reconstructions. The accuracy of the models is contingent on the quality of the input data and the strategy used in the fusion of image and navigation information.