A work cell and method for automatically separating objects disposed in 3D clusters includes dispensing the objects onto a horizontal conveying surface to form a 2D array, reforming the 2D array into a 1D stream in which the objects move in single-file in a predefined moving direction, utilizing a vision-based or other stationary sensing system to identify a selected target object in the 1D stream as the target object passes through an image capture (sensing) region, calculating trajectory data defining the target object's time-based position in the 1D stream, and then utilizing the trajectory data to control a robot arm or other object removal mechanism such that only the selected object is forcibly removed (e.g., swiped or picked-up) from the horizontal conveying surface. A continuous-loop-type conveying mechanism includes two parallel conveyor-belt-type conveying structures and associated belt-switching structures. An AI-powered vision system identifies new object shapes during preliminary learning phases.

The invention concerns a device for obtaining an occlusal registration of a patient; a method for obtaining an occlusal registration of a patient; and a method for dental procedure planning, such as dental implant planning. Radiopaque markers are advantageously applied to improve the devices, methods, and outcomes related to dental procedures.

An apparatus and a method for detecting a three-dimensional object includes a camera configured for obtaining a 2D image, and a controller electrically connected to the camera, and the controller extracts 2D information and 3D information for at least one object from the 2D image, and detects 3D object information by utilizing the 2D information and the 3D information.

Disclosed are techniques for determining shroud size of a fan. The techniques receive by a computer processing system digital data of a three-dimensional representation of a shroud of an axial fan, partition the received data into a first partition corresponding to a shroud segment and a second partition corresponding to a fan segment. determine a shroud boundary ring for the shroud segment and a viewing angle of the shroud boundary ring, apply to an image of the first partition a beam shooting process to determine the shroud diameter, determine if there are pixels in the image, which have values that produce signals indicating that the pixels are coincident with portions of the shroud and when signal is detected, calculate the shroud diameter. One aspect includes using the determined should size opening for performing a flow simulation.

A method for processing an image, which is performed by an image processing apparatus, is provided. The method includes acquiring a first image including an object and a second image including an object identical to the object in the first image under the same condition, acquiring three-dimensional direction information of a specific part of the object in the first image, and providing a three-dimensionally processed image by three-dimensionally rotating the object in the second image by an angle that corresponds to the acquired three-dimensional direction information of the specific part of the object in the first image.

The present disclosure proposes a computer implemented of object recognition of an object to be identified using a method for reconstruction of a 3D point cloud. The method comprises the steps of acquiring, by a mobile device, a plurality of pictures of said object, sending the acquired pictures to a cloud server, reconstructing, by the cloud server, a 3D points cloud reconstruction of the object, performing a 3D match search in a 3D database using the 3D points cloud reconstruction, to identify the object, the 3D match search comprising a comparison of the reconstructed 3D points cloud of the object with 3D points clouds of known objects stored in the 3D database.

A background scenery portion may be identified in each of a plurality of image sets of an object, where each image set includes images captured simultaneously from different cameras. A correspondence between the image sets may determined, where the correspondence tracks control points associated with the object and present in multiple images. A multi-view interactive digital media representation of the object that is navigable in one or more dimensions and that includes the image sets may be generated and stored.

A system for modeling a three-dimensional structure utilizing two-dimensional segments comprising a memory and a processor in communication with the memory. The processor extracts a plurality of two-dimensional segments corresponding to the three-dimensional structure from a plurality of images indicative of different views of the three-dimensional structure. The processor determines a plurality of three-dimensional candidate segments based on the extracted plurality of two-dimensional segments and adds the plurality of three-dimensional candidate segments to a three-dimensional segment cloud. The processor transforms the three-dimensional segment cloud into a wireframe indicative of the three-dimensional structure by performing a wireframe extraction process on the three-dimensional segment cloud.

A device and a method for contactless fingerprint acquisition is provided. The contactless fingerprint acquisition device includes a housing including a finger scanning area for at least one finger; at least two image capturing devices located in the housing and arranged in a predetermined baseline distance, each image capturing device having an optical axis in a predetermined angle with the vertical direction; and, a lighting unit in the housing for illuminating the at least one finger. The at least two image capturing devices are operable to acquire a plurality of partial fingerprint images of the at least one finger, and the plurality of partial fingerprint images correspond to different portions of the at least one finger.

A method of 3D object detection using an object detection neural network includes: receiving one or more monocular images; extracting 2D feature maps from each one of the one or more monocular images by passing the one or more monocular images through a 2D feature extracting part of the object detection neural network, generating an averaged 3D voxel volume based on the 2D feature maps, extracting a 2D representation of 3D feature maps from the averaged 3D voxel volume by passing the averaged 3D voxel volume through an encoder of a 3D feature extracting part of the object detection neural network, and performing 3D object detection as 2D object detection in a Bird's Eye View (BEV) plane, the 2D object detection in the BEV plane being performed by passing the 2D representation of 3D feature maps through thane outdoor object detecting part of the object detection neural network.