Abstract: A method for an image capturing device includes: acquiring a first image of a target object; extracting coordinate information of a first 2D key point corresponding to the target object; acquiring a second image of the target object; acquiring coordinate information of a second 2D key point in the second image according to the coordinate information of the first 2D key point, the first 2D key point and the second 2D key point being the same key point in the target object; acquiring coordinate information of a 3D key point corresponding to the target object, the 3D key point being a key point obtained after a triangulation operation; and determining camera posture information of the second image according to the coordinate information of the first 2D key point, the coordinate information of the second 2D key point, the coordinate information of the 3D key point, and a 3D-2D projection.

Abstract: A relocalization method includes: obtaining, by a front-end program run on a device, a target image acquired after an ith marker image in the plurality of marker images; determining, by the front-end program, the target image as an (i+1)th marker image when the target image satisfies a relocalization condition, and transmitting the target image to a back-end program; performing, by the front-end program, feature point tracking on a current image acquired after the target image relative to the target image to obtain a first pose parameter. The back-end program performs relocalization on the target image to obtain a second pose parameter, and transmits the second pose parameter to the front-end program. The front-end program calculates a current pose parameter of the current image according to the first pose parameter and the second pose parameter.

Abstract: A method for determining a pose of an image capturing device is performed at an electronic device. The electronic device acquires a plurality of image frames captured by the image capturing device, extracts a plurality of matching feature points from the plurality of image frames and determines first position information of each of the matching feature points in each of the plurality of image frames. After estimating second position information of each of the matching feature points in a current image frame in the plurality of image frames by using the first position information of each of the matching feature points extracted from a previous image frame in the plurality of image frames, the electronic device determines a pose of the image capturing device based on the first position information and the second position information of each of the matching feature points in the current image frame.

Abstract: A three-dimensional face model generation method is provided. The method includes: obtaining an inputted three-dimensional face mesh of a target object; aligning the three-dimensional face mesh with a first three-dimensional face model of a standard object according to face keypoints; performing fitting on the three-dimensional face mesh and a local area of the first three-dimensional face model, to obtain a second three-dimensional face model after local fitting; and performing fitting on the three-dimensional face mesh and a global area of the second three-dimensional face model, to obtain a three-dimensional face model of the target object after global fitting.

Abstract: This application provides a three-dimensional (3D) expression base generation method performed by a computer device. The method includes: obtaining image pairs of a target object in n types of head postures, each image pair including a color feature image and a depth image in a head posture; constructing a 3D human face model of the target object according to then image pairs; and generating a set of expression bases of the target object according to the 3D human face model of the target object. According to this application, based on a reconstructed 3D human face model, a set of expression bases of a target object is further generated, so that more diversified product functions may be expanded based on the set of expression bases.

Abstract: Embodiments of this application disclose an artificial intelligence-based (AI-based) animation character control method. When one animation character has a corresponding face customization base, and one animation character has no corresponding face customization base, the animation character having the face customization base may be used as a driving character, and the animation character having no face customization base may be used as a driven character.

Abstract: Embodiments of this application disclose a position and pose determining method performed at an electronic device. The method includes: acquiring, by tracking a first feature point extracted from a marked image, position and pose parameters of a first image captured by a camera relative to the marked image; extracting a second feature point from the first image in a case that the first image fails to meet a feature point tracking condition; and acquiring, by tracking the first feature point and the second feature point, position and pose parameters of a second image captured by the camera relative to the marked image, and determining a position and a pose of the camera according to the position and pose parameters, the second image being an image captured by the camera after the first image.

Abstract: A method for an image capturing device includes: acquiring a first image of a target object; extracting coordinate information of a first 2D key point corresponding to the target object; acquiring a second image of the target object; acquiring coordinate information of a second 2D key point in the second image according to the coordinate information of the first 2D key point, the first 2D key point and the second 2D key point being the same key point in the target object; acquiring coordinate information of a 3D key point corresponding to the target object, the 3D key point being a key point obtained after a triangulation operation; and determining camera posture information of the second image according to the coordinate information of the first 2D key point, the coordinate information of the second 2D key point, the coordinate information of the 3D key point, and a 3D-2D projection.

Abstract: This application discloses a repositioning method performed by an electronic device in a camera pose tracking process, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired by the camera after an ith anchor image in a plurality of anchor images; obtaining an initial feature point and an initial pose parameter in a first anchor image in the plurality of anchor images in a case that the current image satisfies a repositioning condition; performing feature point tracking on the current image relative to the first anchor image, to obtain a target feature point; calculating a pose change amount of a camera from a first camera pose to a target camera pose according to the initial feature point and the target feature point; and performing repositioning according to the initial pose parameter and the pose change amount to obtain a target pose parameter.

Abstract: This application disclose an artificial intelligence (AI) based animation character drive method. A first expression base of a first animation character corresponding to a speaker is determined by acquiring media data including a facial expression change when the speaker says a speech, and the first expression base may reflect different expressions of the first animation character. After target text information is obtained, an acoustic feature and a target expression parameter corresponding to the target text information are determined according to the target text information, the foregoing acquired media data, and the first expression base. A second animation character having a second expression base may be driven according to the acoustic feature and the target expression parameter, so that the second animation character may simulate the speaker's sound and facial expression when saying the target text information, thereby improving experience of interaction between the user and the animation character.

Abstract: This application discloses a repositioning method performed by an electronic device in a camera pose tracking process, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired by the camera after an ith anchor image in a plurality of anchor images; selecting a target keyframe from a keyframe database according to Hash index information in a case that the current image satisfies a repositioning condition; performing second repositioning on the current image relative to the target keyframe; and calculating a camera pose parameter of a camera during acquisition of the current image according to a positioning result of the first repositioning and a positioning result of the second repositioning. In a case that there are different keyframes covering a surrounding area of a camera acquisition scene, it is highly probable that repositioning can succeed, thereby improving the success probability of a repositioning process.

Abstract: Embodiments of this application disclose a position and attitude determining method. The method includes acquiring, by tracking a feature point of a first marked image, position and attitude parameters of an image captured by a camera; using a previous image of a first image as a second marked image in response to the previous image of the first image meeting a feature point tracking condition and the first image failing to meet the feature point tracking condition; acquiring, position and attitude parameters of the image captured by the camera relative to the second marked image; acquiring position and attitude parameters according to the position and attitude parameters of the image relative to the second marked image and position and attitude parameters of each marked image relative to a previous marked image; and determining a position and an attitude of the camera according to the position and attitude parameters.

Abstract: A system includes an optical element configured to separate light into a first light beam and a second light beam, a first optical module configured to capture a first image having a first field of view from the first light beam, a second optical module configured to capture a second image having a second field of view different from the first field of view from the second light beam, and one or more processors configured to generate a scaled image by scaling one of the first image or the second image, and generate a combined image by fusing the scaled image and an unscaled one of the first image or the second image.

Abstract: A computer application method for generating a three-dimensional (3D) face model is provided, performed by a face model generation model running on a computer device, the method including: obtaining a two-dimensional (2D) face image as input to the face model generation model; extracting global features and local features of the 2D face image; obtaining a 3D face model parameter based on the global features and the local features; and outputting a 3D face model corresponding to the 2D face image based on the 3D face model parameter.

Abstract: An image processing method and apparatus, a computer-readable medium, and an electronic device are provided. The image processing method includes: respectively projecting, according to a plurality of view angle parameters corresponding to a plurality of view angles, a face model of a target object onto a plurality of face images of the target object acquired from the plurality of view angles, to determine correspondences between regions on the face model and regions on the face image; respectively extracting, based on the correspondences and a target region in the face model that need to generate a texture image, images corresponding to the target region from the plurality of face images; and fusing the images that correspond to the target region and that are respectively extracted from the plurality of face images, to generate the texture image.

Abstract: This application provides a method for configuring parameters of a three-dimensional face model. The method includes: obtaining a reference face image; identifying a key facial point on the reference face image to obtain key point coordinates as reference coordinates; and determining a recommended parameter set in a face parameter value space according to the reference coordinates. The first projected coordinates are projected coordinates of the key facial point obtained by projecting a three-dimensional face model corresponding to the recommended parameter set onto a coordinate system. The proximity of the first projected coordinates to the reference coordinates meets a preset condition.

Abstract: A system includes an optical element configured to separate light into a first light beam and a second light beam, a first optical module configured to capture a first image having a first field of view from the first light beam, a second optical module configured to capture a second image having a second field of view different from the first field of view from the second light beam, and one or more processors configured to generate a scaled image by scaling one of the first image or the second image, and generate a combined image by aligning the scaled image and an unscaled one of the first image or the second image.

Abstract: Embodiments of this application disclose a method for determining camera pose information of a camera of a mobile terminal. The method includes: obtaining a first image, a second image, and a template image, the first image being a previous frame of image of the second image, the first image and the second image being images including a respective instance of the template image captured by the mobile terminal using the camera at a corresponding spatial position; determining a first homography between the template image and the second image; determining a second homography between the first image and the second image; and performing complementary filtering processing on the first homography and the second homography, to obtain camera pose information of the camera, wherein the camera pose information of the camera represents a spatial position of the mobile terminal when the mobile terminal captures the second image using the camera.

Abstract: A method of image processing includes obtaining depth information respectively corresponding to one or more objects in an image frame captured by an imaging system based on spatial configuration of the imaging system, calculating one or more rendering parameters associated with one of the one or more objects in the image frame based on at least the depth information of the one or more objects, and rendering the image frame using the one or more rendering parameters to obtain a processed image frame. The processed image frame includes an in-focus region and an out-of-focus region relative to the one of the one or more objects.

Abstract: Embodiments of this application disclose a method for determining camera pose information of a camera of a mobile terminal. The method includes: obtaining a first image, a second image, and a template image; performing feature point detection on a first feature point of the template image and a second feature point of the second image, to obtain a first homography; determining a first target homography according to a first optical flow feature point in the first image and a second optical flow feature point in the second image, and determining a second homography according to the first target homography and a second target homography; and performing complementary filtering processing on the first homography and the second homography, to obtain camera pose information of the camera. In the embodiments of this application, complementary filtering processing may be performed on two homographies obtained in a camera pose tracking process.