Abstract: The present invention provides a system and method of automatic detection of structure integrity threats. A threat detection engine detects integrity threats in structures, such as underwater structures, and segments the structures in an image using convolutional neural networks (“CNN”). The threat detection engine may include a dataset module, a CNN training module, a segmentation map module, a semi-supervision module, and an efficiency module. The threat detection engine may train a deep learning model to detect anomalies in videos. To do so, a dataset module with videos may be used where the dataset module includes annotations detailing at what timestamps one or more anomalies are visible.

Abstract: The present invention provides systems and methods for simultaneous localization and mapping from video with adversarial shape prior learning in real-time. For example, an unsupervised direct and dense SLAM may learn a geometry prior from data. Given a video sequence, a depth map of a target frame, as well as the target frame and the camera motions between the target frame and all the remaining frames may be output. Further, by fusing a camera motion estimate with a positional sensor's output, positional drift and the need for loop closure can be avoided.

Abstract: The present invention provides a system and method of position estimation for remotely operated vehicles, even in noisy environments. In some embodiments, a position estimation engine includes a 2D projection module, a registration module, a position estimation module, and an efficiency module. The improved position estimation starts with a real frame from a video and a virtual image that is the projection of the 3D elements given the ROV's noisy position. The position estimate begins by projecting each of the visible structures individually and then registers them with the real image. Then the 2D transformation resulting from the registration process is used to estimate the 3D ROV's position. Then, the ROV's position estimates are robustly combined. Because this position estimation needs to run in real-time or near real-time, an efficiency module improves the efficiency of the position estimation.

Abstract: The present invention provides a system and method of utilizing superimposed 3D imagery for remotely operated vehicles, namely 3D, reconstructed images of the environment of the ROV. In another aspect, it includes generating a virtual video of 3D elements in the operation environment, synchronizing the angle and position of the camera of a virtual video with the angle and position of a real camera, superimposing the virtual video and the real video from the real camera; superimposing these video feeds such that one is manipulated to show transparencies in areas of less interest, in order to show through the other video. It furthermore may include superimposing information, whether graphic, textual or both on to the hybrid virtual-real 3D imagery. The subject invention is also networked, such that the immersive visual interface described above is accessible to a plurality of users operating from a plurality of locations.

Abstract: The present invention provides a system and method of utilizing superimposed 3D imagery for remotely operated vehicles, namely 3D, reconstructed images of the environment of the ROV. In another aspect, it includes generating a virtual video of 3D elements in the operation environment, synchronizing the angle and position of the camera of a virtual video with the angle and position of a real camera, superimposing the virtual video and the real video from the real camera; superimposing these video feeds such that one is manipulated to show transparencies in areas of less interest, in order to show through the other video. It furthermore may include superimposing information, whether graphic, textual or both on to the hybrid virtual-real 3D imagery. The subject invention is also networked, such that the immersive visual interface described above accessible to a plurality of users operating from to plurality of locations.

Abstract: The present invention provides a system and method of utilizing superimposed 3D imagery for remotely operated vehicles, namely 3D, reconstructed images of the environment of the ROV. In another aspect, it includes generating a virtual video of 3D elements in the operation environment, synchronizing the angle and position of the camera of a virtual video with the angle and position of a real camera, superimposing the virtual video and the real video from the real camera; superimposing these video feeds such that one is manipulated to show transparencies in areas of less interest, in order to show through the other video. It furthermore may include superimposing information, whether graphic, textual or both on to the hybrid virtual-real 3D imagery. The subject invention is also networked, such that the immersive visual interface described above is accessible to a plurality of users operating from a plurality of locations.