Image processing method and apparatus

    公开(公告)号:US11288838B2

    公开(公告)日:2022-03-29

    申请号:US16531105

    申请日:2019-08-04

    IPC分类号: G06T7/73 G06T7/246

    摘要: An image processing method and an image processing includes, when a current frame contains a target picture, taking the current frame as a reference frame for tracking and taking a set of matching points in the current frame, which match the target picture as an initial set of tracking points, to perform tracking of the target picture; obtaining a next frame and determining a set of tracking points of the next frame based on the initial set of tracking points; determining whether the number of tracking points in the set of tracking points is less than a first preset threshold; and, when the number of tracking points in the set of tracking points is less than the first preset threshold, determining supplementary tracking points and adding the supplementary tracking points to the set of tracking points.

    IMAGE PROCESSING METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20210012153A1

    公开(公告)日:2021-01-14

    申请号:US16498145

    申请日:2019-01-15

    IPC分类号: G06K9/62 G06F16/51 G06F16/55

    摘要: An image processing method includes acquiring a set of training images, and extracting a visual feature of each training image in the set of training images. The method includes clustering the visual feature, generating a visual dictionary composed of cluster centers serving as visual words, and adding 1 to the number of the visual dictionaries. The method includes determining whether the number of the visual dictionaries is equal to a predetermined number, and outputting the predetermined number of visual dictionaries generated if the determination result is yes, otherwise determining, from the visual dictionary, a visual word nearest to the visual feature. The method includes calculating a residual between the visual feature and the visual word nearest to the visual feature, determining the residual as the new visual feature, and returning to clustering the visual feature, generating a visual dictionary, and adding 1 to the number of the visual dictionaries.