A method for characterizing a pose estimation system includes: receiving, from a pose estimation system, first poses of an arrangement of objects in a first scene; receiving, from the pose estimation system, second poses of the arrangement of objects in a second scene, the second scene being a rigid transformation of the arrangement of objects of the first scene with respect to the pose estimation system; computing a coarse scene transformation between the first scene and the second scene; matching corresponding poses between the first poses and the second poses; computing a refined scene transformation between the first scene and the second scene based on coarse scene transformation, the first poses, and the second poses; transforming the first poses based on the refined scene transformation to compute transformed first poses; and computing an average rotation error and an average translation error of the pose estimation system based on differences between the transformed first poses and the second poses.

A method of registering geological data at a formation core tracking system includes, at the tracking system, registering a formation core provided within a field of view of an optical imaging system of the tracking system; tracking the orientation of the formation core relative to the tracking system and the distance of the formation core relative to the tracking system; obtaining data associated with a first section of the formation core which is located at a predetermined distance from the tracking system, displaying the data together with an image of the formation core such that an augmented reality image is provided on a display device of the tracking system, changing the distance between the tracking system and the core; and updating the displayed data by obtaining data associated with a second section of the formation core which is located at said predetermined distance from the tracking system.

A face image processing method and apparatus, a face image display method and apparatus, and a device are provided, belonging to the technical field of image processing. The method includes: acquiring a first face image of a person; invoking an age change model to predict a texture difference map of the first face image at a specified age, the texture difference map being used for reflecting a texture difference between a face texture in the first face image and a face texture of a second face image of the person at the specified age; and performing image processing on the first face image based on the texture difference map to obtain the second face image.

This application provides a method and an apparatus for interaction processing of a virtual item, an electronic device, and a computer-readable storage medium. The method includes displaying at least one idle virtual item in a virtual scene; moving a first virtual object in the virtual scene in response to a movement operation on the first virtual object; displaying a pickable prompt of the idle virtual item when there is no obstacle between the idle virtual item and the first virtual object; and controlling the first virtual object to pick up the idle virtual item in response to a picking-up operation by the first virtual object.

An image registration apparatus including at least one processor and configured to project, to a first model, a first image generated based on an image obtained from a first camera to generate a first intermediate image, to map the first intermediate image to a first output model to generate a first output image, to project, to a second model, a second image generated based on an image obtained from a second camera to generate a second intermediate image, to map the second intermediate image to a second output model to generate a second output image, and to determine a match rate between the first output image and the second output image and transform at least one of the first model and the second model based on a determined match rate and a preset reference match rate.

A 3D calling system can provide 3D calls in various modes according to transitions and can provide affordances (i.e., visual or auditory cues) to improve 3D call image capturing. The 3D calling system of a recipient in a 3D call can display a hologram (from images captured by an external capture device (ECD)) or avatar of a sending call participant in a variety of ways, such as by making them “world-locked,” “ECD-locked,” or “body-locked.” The selection of a 3D call mode can be based on factors such as whether an ECD is active, whether the ECD is in motion, and user selections. In various cases, the 3D calling system can trigger various affordances to improve the quality of the images captured by the sender’s ECD, such as a displayed virtual object and/or an auditory cue, either signaling to the user that a current ECD configuration is non-optimal and/or providing instructions for an improved ECD configuration.

Three-dimensional (3D) modeling systems and methods are described for automatically generating photorealistic, virtual 3D package and product models from two-dimensional (2D) imaging assets and dimensional data. The 3D modeling systems and methods include storing, by a memory with one or more processors, 2D imaging assets and dimensional datasets, obtaining, with an imaging asset manipulation script, a shape classification defining a real-world product or product package to be virtually modeled in 3D space, generating, with the imaging asset manipulation script, a spline based on an alpha channel extracted from a 2D imaging asset depicting the real-world product or package, and generating, with the imaging asset manipulation script, a parametric model based on the spline, the dimensional dataset, and the shape classification. A virtual 3D model is generated based on the parametric model and rendered, via a graphical display or environment, as a photorealistic image representing the real-world product or product package.

The disclosed systems, components, methods, and processing steps are directed to determining user-item fit characteristics of an item for a user body part by accessing a three-dimensional (3D) reconstructed model of the user body part, accessing information about one or more 3D reference models of the item, the information for each 3D reference model including respective dimensional measurement, spatial, and geometrical attributes, performing a 3D matching process based on the 3D reconstructed model and the accessed information of the one or more 3D reference models to determine a best-fitting 3D reference model from the one or more 3D reference models, integrating the best-fitting 3D reference model with the 3D reconstructed model to provide a 3D best fit representation and displaying the 3D best fit representation along with visual indications of user-item fit characteristics.

When three-dimensional audio is produced by using headphones, particular HRTF-filters are used to modify sound for the left and right channels of the headphone. As the morphology of every ear is different, it is beneficial to have HRTF-filters particularly designed for the user of headphones. Such filters may be produced by deriving ear geometry from a plurality of images taken with an ordinary camera, detecting necessary features from images and fitting said features to a model that has been produced from accurately scanned ears comprising representative values for different sizes and shapes. Taken images are sent to a server (52) that performs the necessary computations and submits the data further or produces the requested filter.

A method and an apparatus for processing an image are provided. The method may include: acquiring a set of image sequences, the set of image sequences including a plurality of image sequence subsets divided according to similarity measurements between image sequences, each image sequence subset including a basic image sequence and other image sequence, wherein a first similarity measurement corresponding to the basic image sequence is greater than or equal to a first similarity measurement corresponding to the other image sequence; creating an original three-dimensional model using the basic image sequence; and creating a final three-dimensional model using the other image sequence based on the original three-dimensional model.