There is provided an image processing system and method for identifying a user. The system comprises a processor configured to identify a first user in an image, determine a plurality of characteristic vectors associated with the first user, compare the characteristic vectors associated with the first user with a plurality of predetermined characteristic vectors associated with a plurality of users including the first user, and identify the first user based on the comparison.

An information processing method and an electronic device are provided. The method is performed by a first wearable device, where the first wearable device includes a first image collector, and the method includes: obtaining a second face image by the first image collector and receiving a first face image from the second wearable device in a case that the first wearable device and a second wearable device are in a preset positional relationship; and processing first target information from the second wearable device in a case that the first face image matches the second face image.

A video processing method, comprising: according to the scenario, editing a video to be edited, and obtaining a target video (S100); acquiring feature parameters of the target video (S200); generating, according to the feature parameters, a keyword of the target video (S300); and associatively storing the keyword and the target video (S400).

This application provides a video information processing method performed by an electronic device. The method includes: determining a video image frame set corresponding to each of a first video and a second video, respectively; determining a static stitching region corresponding to image frames in the video image frame set; cropping the image frames in the video image frame set according to the static stitching region, and determining an image feature vector for the video based on a corresponding cropping result using a video information processing model; and determining a similarity between the first video and the second video based on an image feature vector corresponding to the first video and an image feature vector corresponding to the second video.

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 information processing device (200A, 200B, and 200C) according to the present disclosure includes a control unit (220, 220B, and 220C). The control unit (220, 220B, and 220C) acquires a captured image of a target imaged by a sensor. The captured image is an image obtained from reflected light of light emitted to the target from a plurality of light sources arranged at different positions, respectively. The control unit (220, 220B, and 220C) extracts a flat region from the captured image based on a luminance value of the captured image. The control unit (220, 220B, and 220C) calculates shape information regarding a shape of a surface of the target based on information regarding the sensor and the flat region of the captured image.

A face authentication apparatus (50) includes an image generation unit (102) that generates a first image by capturing an image of a person, a control unit (104) that, when the first image does not satisfy a criterion for face collation, controls lighting and causes the image generation unit (102) to generate a second image by capturing an image of the person again, and a face authentication unit (52) that executes face authentication by using the second image.

A computer implemented method and apparatus determines a body region represented by medical imaging data stored in a first image file. The first image file further stores one or more attributes each having an attribute value comprising a text string indicating content of the medical imaging data. One or more of the text strings of the first image file are obtained and input into a trained machine learning model, the machine learning model having been trained to output a body region based on an input of one or more such text strings. The output from the trained machine learning model is obtained thereby to determine the body region represented by the medical imaging data. Also disclosed are methods of selecting one or more sets of second medical imaging data as relevant to first medical imaging data.

An electronic device is provided. The electronic device includes a memory, an image sensor including light receiving elements each including at least two sub light receiving elements, and an image signal processor. The image signal processor is configured to obtain images corresponding to light from outside by using the image sensor, the images including at least a raw image, a first sub image, and a second sub image, the first sub image being an image corresponding to light detected by at least one first sub light, the second sub image being an image corresponding to light detected by at least one second sub light, identify a luminance ratio between the first sub image and the second sub image, identify a defect in the raw image, based on the luminance ratio, and perform a function corresponding to a type of the defect.

A method of processing an image, an electronic device, and a storage medium, which relate to the artificial intelligence field, in particular to fields of computer vision and intelligent transportation technologies. The method includes: determining at least one key frame image in a scene image sequence captured by a target camera; determining a camera pose parameter associated with each key frame image in the at least one key frame image, according to a geographic feature associated with the key frame image; and projecting each scene image in the scene image sequence to obtain a target projection image according to the camera pose parameter associated with the key frame image, so as to generate a scene map based on the target projection image. The geographic feature associated with any key frame image indicates localization information of the target camera at a time instant of capturing the corresponding key frame image.