Embodiments of the present disclosure set forth a method to augment medical scan information associated with a target object on a first extended reality image. The method includes obtaining a three-dimensional image associated with the target object, identifying a first set of three-dimensional feature points from the three-dimensional image, identifying anatomical points based on the first set of three-dimensional feature points, obtaining the first extended reality image associated with the anatomical points; selecting a second set of three-dimensional feature points from the first extended reality image, performing a first image matching between the first set of three-dimensional feature points and the second set of three-dimensional feature points, and superimposing the three-dimensional image on the first extended reality image based on the first image matching.

Embodiments provide an image processing method, program, and apparatus, for using a database of data manifestations of objects to identify those objects in image data representing a domain or space containing objects to be identified. Embodiments leverage 3D vector field representations of both the domain or space, and of the objects, to perform the recognition. Embodiments annotate the image data with information relating to the identified objects, and/or replace portions of the image data with a data manifestation of the recognised object imported from the database.

This invention relates to a computer implemented method for detecting correspondence of a built structure with a designed structure. The method comprises the steps of: receiving an unorganized point cloud (PC) of the built structure, the unorganized PC containing a data set with a plurality of data points, each of which has an RGB value associated therewith; receiving an Industry Foundation Classes (IFC) model of the designed structure, the IFC model including an IFC schema file classifying all object types and object characteristics in the IFC model, the object characteristics including a model object RGB value; integrating the unorganized PC with the IFC model and generating a semantic point cloud by overwriting the RGB value of the data point in the PC with the model object RGB value from the IFC model. In this way, the resulting PC will be easier to evaluate and the evaluation will be more effective.

A method for matching a reference object and a test object includes providing a test object in a field of sensing of at least one sensor disposed at a vehicle. A volume match is determined based on a volume of the reference object and a volume of the test object. A distance match is determined based on a center and orientation of the reference object and a center and orientation of the test object. An angle match is determined based on a yaw angle of the reference object and a yaw angle of the test object. A superposition of the volume match, the distance match, and the angle match is determined based on a multiplication of the volume match, the distance match, and the angle match. A degree of matching of the reference object and the test object is determined based on the superposition.

Motion-related 3D feature extraction by receiving a set of sequential radar signal data frames associated with a subject, determining radar signal amplitude and phase for each data frame, determining radar signal phase changes between sequential data frames, and extracting, by a trained machine learning model, one or more three-dimensional features from the sequential radar signal data frames according to the radar signal amplitude and the radar signal phase changes between sequential data frames.

Minimally-invasive spinal inventions are often performed using fluoroscopic imaging methods, which can give a real-time impression of the location of a surgical instrument, at the expense of a small field of view. When operating on a spinal column, a small field of view can be a problem, because a medical professional is left with no reference vertebra in the fluoroscopy image, from which to identify a vertebra, which is the subject of the intervention. Identifying contiguous vertebrae is difficult because such contiguous vertebrae are similar in shape. However, characteristic features, which differentiate one vertebra from other vertebra, and which are visible in the fluoroscopic view, may be used to provide a reference.

The invention notably relates to a computer-implemented method for querying a database. The database comprises 3D modeled objects that each represent a mechanical part. The database further comprises, for each 3D modeled object, a respective morphology signature. The method comprising: providing a query that includes a morphology criterion; returning, as results of the query, respective 3D modeled objects of the database, a respective 3D modeled object being returned based on an extent to which the respective 3D modeled object has a morphology signature that respects the morphology criterion. Such a method improves the field of searching mechanical parts in a database.

The system and method deal with three-dimensional (3D) scanning technology which produces object representations which permit rapid, highly-accurate part identification which is not afforded by traditional two-dimensional (2D) camera imaging. The system and method are applicable to any field wherein repair/replacement parts are needed, such as the plumbing, automotive, fastener, marine, window, door, etc. fields

Disclosed are systems and method for determining information related to building materials based on determined measurements from a multi-dimensional building model comprising features and elements embodying such materials and measurements. The multi-dimensional model may be based on a plurality of received images, such as ground-based images of a building. The multi-dimensional model may be scaled, or a scale extracted based on data of the model. The multi-dimensional model may comprise architectural elements, and the scale used to determine measurements of such architectural elements. With the scaled measurements of the architectural elements in the model, product information related to multi-dimensional model and its elements may be derived and combined in alternative means.

Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects. When all relevant annotation information has been gathered and associated with model objects, the system can create a list of materials that can be used for future purposes, such as repair and/or reconstruction of real-world structures and property.