# UV3D: Underwater Video Stream 3D Reconstruction Based on Efficient Global SFM
###### Abstract
Although the incremental approach is more robust, the efficiency and accuracy are not as good as the global approach, and the cumulative error also easily causes scene drift. If the robustness of global SFM can be improved, we could obtain a better reconstruction effect at a faster speed. The application of global SFM in underwater 3D reconstruction currently is still very limited, so in this paper we will use the more rapid and robust global SFM for the 3D reconstruction of underwater targets, and we will also propose a complete reconstruction process for underwater environments. For underwater 3D reconstruction tasks, sonar images lack color information, meaning optical images are more conducive to obtaining the complete picture of the target. There are many challenges for underwater 3D reconstruction. On the one hand, the quality of the image significantly influences the reconstruction results; however, the underwater images may have problems such as noise, blur, and color degradation [16; 17], meaning image enhancement and color correction are necessary prior to reconstruction [18]. To restore images degraded by the underwater environment, many scientists have proposed many solutions. For instance, an unsupervised method was raised by [PERSON] et al. [19] in 2015, which is robust and simple at the same time. Additionally, some supervised methods [20; 21] based on training data have been presented in recent years. On the other hand, the propagation speed of an acoustic wave is five times slower than that on land; along with the large amount of noise and narrow bandwidth [22], the efficiency of underwater data transmission is extremely low. To address the problems described above, and because of the rich detailed information available from optical imaging and superior transmission efficiency of acoustic systems, we present a terminal image processing strategy based on an underwater acousto-optical fusion imaging system [23]. After the sonar on the leader ship detects the target, the AUV carrying the optical camera will approach the target and obtain the three-dimensionalstructure of the target from the video stream, which is completed on the terminal AUV to implement the smart ocean concept [24]. After this, the processed data are sent to the leader ship through the acoustic wave. In general, the core of this article is focused on how to reconstruct the three-dimensional structure of the target object and compress the data from the continuous optical images collected by the optical camera mounted on the AUV. The process is as follows. Firstly, to obtain the image sequence for SFM, the key frame extraction method is used to obtain key frames from the video stream. The following step is to improve the quality of the images, which is essential for the feature detection of underwater images. In this paper, we use different methods to enhance the images with various disadvantages. In addition, we propose a robust method for rotation averaging during the global SFM process, which improves the efficiency of the 3D point estimation. Finally, we summarize an SFM-PMVS pipeline, and every detail is enumerated. Under this strategy, we improve the data transmission efficiency and make it easier to obtain an overview of the underwater scene.