Abstract: An image registration method includes: acquiring a target image comprising a target object; inputting the target image to a preset network model, and outputting position information and rotation angle information of the target object; obtaining a reference image comprising the target object by querying a preset image database according to the position information and the rotation angle information; and performing image registration on the target image and the reference image to obtain a corresponding position of the target object of the target image in the reference image.

Abstract: The method of the present invention for processing a video comprises: acquiring a first and a second omnidirectional videos having a stereoscopic parallax in a first direction which is a corresponding column direction when the first and the second omnidirectional videos are unfolded by longitude and latitude; and, determining one or two third omnidirectional videos according to the first and the second omnidirectional videos, the second and the third omnidirectional videos having a stereoscopic parallax in a second direction, wherein, if one third omnidirectional video is determined, the second and the third omnidirectional videos have a stereoscopic parallax in the second direction; if two third omnidirectional videos are determined, the two third omnidirectional videos have a stereoscopic parallax in the second direction; and, the second direction is a corresponding row direction when the first and the second omnidirectional videos are unfolded by longitude and latitude.

Abstract: An apparatus for recommending a customer item identifies a purchase tendency of a customer based on an image, determines a recommended item for the customer by selecting a purchase tendency model corresponding to the purchase tendency, and provides information associated with the determined recommended item.

Abstract: A method and apparatus for detecting a moving target, an electronic equipment and a storage medium. The method includes obtaining a first frame image and a second frame image which are adjacent, and a rotation matrix and a translation matrix between the first and second frame images, the first and second frame image include the same moving target; extracting first feature points from the first frame image; determining second feature points corresponding to the first feature points from the second frame image based on the second frame image and the first feature points; determining distances between the second feature points and corresponding polar lines based on the rotation matrix and the translation matrix; determining third feature points located on the moving target based on the distances; and detecting the moving target based on the third feature points.

Abstract: The method of the present invention for processing a video comprises: acquiring a first and a second omnidirectional videos having a stereoscopic parallax in a first direction which is a corresponding column direction when the first and the second omnidirectional videos are unfolded by longitude and latitude; and, determining one or two third omnidirectional videos according to the first and the second omnidirectional videos, the second and the third omnidirectional videos having a stereoscopic parallax in a second direction, wherein, if one third omnidirectional video is determined, the second and the third omnidirectional videos have a stereoscopic parallax in the second direction; if two third omnidirectional videos are determined, the two third omnidirectional videos have a stereoscopic parallax in the second direction; and, the second direction is a corresponding row direction when the first and the second omnidirectional videos are unfolded by longitude and latitude.

Abstract: A method and apparatus for detecting a moving target, an electronic equipment and a storage medium. The method includes obtaining a first frame image and a second frame image which are adjacent, and a rotation matrix and a translation matrix between the first and second frame images, the first and second frame image include the same moving target; extracting first feature points from the first frame image; determining second feature points corresponding to the first feature points from the second frame image based on the second frame image and the first feature points; determining distances between the second feature points and corresponding polar lines based on the rotation matrix and the translation matrix; determining third feature points located on the moving target based on the distances; and detecting the moving target based on the third feature points.

Abstract: Disclosed are a pose estimation methods and apparatuses of displaying a virtual object using an estimated pose. The pose estimation method includes receiving an input image and estimating pose information of an object from the input image based on local information of the object.

Abstract: Disclosed is an object pose estimating method and apparatus. The pose estimating method includes acquiring a two-dimensional (2D) image corresponding to an object, extracting a global visual feature and a local geometric feature of the object in the 2D image, and estimating a three-dimensional (3D) pose of the object based on the global visual feature and the local geometric feature.

Abstract: An image processing apparatus includes a calculator configured to calculate a respective position offset for each of a plurality of candidate areas in a second frame based on a position of a basis image in a first frame and a determiner configured to determine a final selected area that includes a target in the second frame based on a respective weight allocated to each of the plurality of candidate areas and the calculated respective position offset.

Abstract: A method of processing a stereoscopic video includes determining whether a current frame of a stereoscopic video is a video segment boundary frame; determining whether an image error is included in the current frame when the current frame is the video segment boundary frame; and processing the current frame by removing, from the current frame, a post inserted object (PIO) included in the current frame when the image error is included in the current frame.

Abstract: A method and apparatus for correcting an image error in a naked-eye three-dimensional (3D) display may include controlling a flat-panel display displaying a stripe image, calculating a raster parameter of the naked-eye 3D display based on a captured stripe image, and correcting a stereoscopic image displayed on the naked-eye 3D display based on the calculated raster parameter, wherein the naked-eye 3D display includes the flat-panel display and the raster.

Abstract: Disclosed are a pose estimation methods and apparatuses of displaying a virtual object using an estimated pose. The pose estimation method includes receiving an input image and estimating pose information of an object from the input image based on local information of the object.

Abstract: Disclosed is an object pose estimating method and apparatus. The pose estimating method includes acquiring a two-dimensional (2D) image corresponding to an object, extracting a global visual feature and a local geometric feature of the object in the 2D image, and estimating a three-dimensional (3D) pose of the object based on the global visual feature and the local geometric feature.

Abstract: An apparatus for recommending a customer item identifies a purchase tendency of a customer based on an image, determines a recommended item for the customer by selecting a purchase tendency model corresponding to the purchase tendency, and provides information associated with the determined recommended item.

Abstract: A feature point positioning apparatus includes a memory storing computer-executable instructions; and one or more processors configured to execute the computer-executable instructions such that the one or more processors are configured to, iteratively update a first form coefficient based on, a nonlinear feature extracted from an image, and a regression factor matrix obtained through training, and detect a position of the feature point of the image based on, the updated first form coefficient, and a statistical form model obtained through training.

Abstract: An image processing apparatus includes a calculator configured to calculate a respective position offset for each of a plurality of candidate areas in a second frame based on a position of a basis image in a first frame and a determiner configured to determine a final selected area that includes a target in the second frame based on a respective weight allocated to each of the plurality of candidate areas and the calculated respective position offset.

Abstract: Apparatuses and methods for processing image are provided. The apparatus includes a processor that generates a target region, including the subject, for each of a first frame image and a second frame image, among the plurality of frame images, extracts first feature points in the target region of the first frame image and second feature points in the target region of the second frame image, calculate disparity information by matching the first feature points extracted from the first frame image and the second feature points extracted from the second frame image and determine a distance between the subject and the image capturing device based on the calculated disparity.

Abstract: A feature point positioning apparatus includes a memory storing computer-executable instructions; and one or more processors configured to execute the computer-executable instructions such that the one or more processors are configured to, iteratively update a first form coefficient based on, a nonlinear feature extracted from an image, and a regression factor matrix obtained through training, and detect a position of the feature point of the image based on, the updated first form coefficient, and a statistical form model obtained through training.

Abstract: A method and apparatus for correcting an image error in a naked-eye three-dimensional (3D) display, the method including controlling a flat-panel display displaying a stripe image, calculating a raster parameter of the naked-eye 3D display based on a captured stripe image, and correcting a stereoscopic image displayed on the naked-eye 3D display based on the calculated raster parameter, wherein the naked-eye 3D display includes the flat-panel display and the raster is disclosed.

Abstract: A method of processing a stereoscopic video includes determining whether a current frame of a stereoscopic video is a video segment boundary frame; determining whether an image error is included in the current frame when the current frame is the video segment boundary frame; and processing the current frame by removing, from the current frame, a post inserted object (PIO) included in the current frame when the image error is included in the current frame.