Methods and apparatus to generate photo-realistic three-dimensional models of a photographed environment are disclosed. An apparatus includes an object position calculator to determine a three-dimensional (3D) position of an object detected within a first image of an environment and within a second image of the environment. The apparatus further includes a 3D model generator to generate a 3D model of the environment based on the first image and the second image. The apparatus also includes a model integrity analyzer to detect a difference between the 3D position of the object and the 3D model. The 3D model generator automatically modifies the 3D model based on the difference in response to the difference satisfying a confidence threshold.

A method of generating a three-dimensional model of an object, is executed by a processor. The method includes executing rendering of the three-dimensional model of the object based on an image captured by the imaging device; and modifying the three-dimensional model.

A projecting apparatus includes a projecting device, an image-capturing device and a processing device. The projecting device projects a reversible structured light code onto a surface. The image-capturing device captures the reversible structured light code projected onto the surface and obtains image data. The processing device is coupled to the projecting device and the image-capturing device. The processing device receives the image data, generates three-dimensional point cloud information by performing decoding on the image data, and obtains scanning shift information corresponding to the projecting device according to the three-dimensional point cloud information and three-dimensional information corresponding to the surface.

In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.

A method of scanning an oral cavity including: acquiring, using an intraoral scanner (IOS) head, without changing a position of the IOS head, a first image of a first region of interest (ROI) and a second image of a second ROI where the first and the second ROIs are of different portions of a dental arch of the oral cavity and do not overlap; reconstructing depth information for the first and the second ROI; and generating a single model of the dental arch by combing the depth information.

This disclosure provides a system and method for producing ultrasound images based on Full Waveform Inversion (FWI). The system captures acoustic/(an)elastic waves transmitted through and reflected and/or diffracted from a medium. The system performs an FWI process in a time domain in conjunction with an accurate wave propagation solver. The system produces 3D maps of physical parameters that control wave propagation, such as shear and compressional wavespeeds, mass density, attenuation, Poisson's ratio, bulk and shear moduli, impedance, and even the fourth-order elastic tensor containing up to 21 independent parameters, which are of significant diagnostic value, e.g., for medical imaging and non-destructive testing.

A method includes, in a processor, receiving example representations of geometrical shapes of a given type of organ. In a training phase, a neural network model is trained using the example representations. In a modeling phase, the trained neural network model is applied to a set of location measurements acquired in an organ of the given type, to produce a three-dimensional model of the organ.

Systems and methods of generating a three-dimensional (3D) reconstruction of a scene or environment surrounding a user of a spatial computing system, such as a virtual reality, augmented reality or mixed reality system, using only multiview images comprising RGB images, and without the need for depth sensors or depth data from sensors. Features are extracted from a sequence of frames of RGB images and back-projected using known camera intrinsics and extrinsic s into a 3D voxel volume wherein each pixel of the voxel volume is mapped to a ray in the voxel volume. The back-projected features are fused into the 3D voxel volume. The 3D voxel volume is passed through a 3D convolutional neural network to refine the and regress truncated signed distance function values at each voxel of the 3D voxel volume.

In one embodiment, a method for generating a three-dimensional (3D) anatomical map, including applying a trained artificial neural network to (a) a set of two-dimensional (2D) fluoroscopic images of a body part of a living subject, and (b) respective first 3D coordinates of the set of 2D fluoroscopic images, yielding second 3D coordinates of the 3D anatomical map, and rendering to a display the 3D anatomical map responsively to the second 3D coordinates.

According to one embodiment, a method, computer system, and computer program product for identifying commercialization opportunities for digital twin resources captured on a sensor is provided. The present invention may include receiving digital content pertaining to a physical asset captured by the sensor; responsive to determining that no digital twin resources within a digital twin content store associated with the physical asset exceed a threshold level of similarity to the digital content, uploading the digital content to the digital twin content store based on a user response to one or more prompts.