Abstract: An image processing method and apparatus, a device and a computer-readable storage medium, wherein the method includes: acquiring a plurality of critical points of regions of an original image, wherein the regions correspond to different body parts in a portrait; according to the plurality of critical points of the regions, determining shape-context-histogram features of the regions of the original image; according to the shape-context-histogram features of the regions of the original image and shape-context-histogram features of predetermined source-material region images of corresponding regions, determining a plurality of cost matrixes for the regions; according to the plurality of cost matrixes for the regions, screening source-material region images that match with each of the regions of the original image from the source-material region images; and splicing the source-material region images that match with each of the regions of the original image, to obtain a target image corresponding to the original

Abstract: A living body detection method and system, and a computer-readable storage medium are disclosed. The living body detection method includes: acquiring a video including an object to be detected; extracting at least two images to be detected from the video, and determining optical flow information according to the at least two images to be detected; dividing each image to be detected into a foreground image and a background image according to the optical flow information; using a classifier to perform category judgment on the foreground image and the background image to obtain a category distribution of the foreground image and a category distribution of the background image; and obtaining a probability that the object to be detected is a living body according to the category distribution of the foreground image and the category distribution of the background image.

Abstract: The present disclosure provides a living body detection method, an electronic device and a computer readable medium. The living body detection method includes: obtaining video images of a target object; extracting a first image and a second image from the video images, wherein the first image is used to represent static information in the video images, and the second image is used to represent position change information of all pixel points in the video images; making a living body analysis on the first image to obtain a first analysis result, making a second body analysis on the second image to obtain a second analysis result, and determining whether the target object is a living body according to the first analysis result and the second analysis result.

Abstract: A living body detection method and system, and a computer-readable storage medium are disclosed. The living body detection method includes: acquiring a video including an object to be detected; extracting at least two images to be detected from the video, and determining optical flow information according to the at least two images to be detected; dividing each image to be detected into a foreground image and a background image according to the optical flow information; using a classifier to perform category judgment on the foreground image and the background image to obtain a category distribution of the foreground image and a category distribution of the background image; and obtaining a probability that the object to be detected is a living body according to the category distribution of the foreground image and the category distribution of the background image.

Abstract: The present disclosure provides a living body detection method, an electronic device and a computer readable medium. The living body detection method includes: obtaining video images of a target object; extracting a first image and a second image from the video images, wherein the first image is used to represent static information in the video images, and the second image is used to represent position change information of all pixel points in the video images; making a living body analysis on the first image to obtain a first analysis result, making a second body analysis on the second image to obtain a second analysis result, and determining whether the target object is a living body according to the first analysis result and the second analysis result.