Disclosed are a fatigue state detection method and apparatus, a medium and a device. The method includes: obtaining image blocks containing an organ area of a target object from a plurality of video frames collected by a camera apparatus disposed in a mobile device, to obtain an image-block sequence that is based on the organ area; determining a fatigue state type of the target object based on the image-block sequence of the organ area; sending the image-block sequence to a cloud server if the fatigue state type meets a first preset type, and rendering the cloud server to detect a fatigue level of the target object based on the image-block sequence; and receiving fatigue level information about the target object that is returned by the cloud server. The present disclosure may improve accuracy of fatigue state detection, thereby helping to improve driving safety of the mobile device.

Sign language information processing method and apparatus, an electronic device and a readable storage medium provided by the present disclosure, achieve real-time collection of language data in a current communication of a user by obtaining voice information and video information collected by a user terminal in real time; and then match a speaking person with his or her speaking content by determining, in the video information, a speaking object corresponding to the voice information; and finally, make it possible for the user to clarify the corresponding speaking object when the user sees AR sign language animation in a sign language video by superimposing and displaying an augmented reality AR sign language animation corresponding to the voice information on a gesture area corresponding to the speaking object to obtain a sign language video. Therefore, it is possible to provide a higher user experience.

A first electronic device according to various embodiments may include: a display; a communication module comprising communication circuitry; a camera module including at least one camera; and a processor. The processor may be configured to: identify a request for measuring a skin condition of a user in a state in which the first electronic device is cradled on a second electronic device; acquire, based on information of the camera module and information regarding at least one light-emitting element included in the second electronic device, control information for controlling output of the at least one light-emitting element; control output of light from the at least one light-emitting element of the second electronic device based on the control information; acquire at least one image including at least a part of a body of the user through the camera module while light is output through the at least one light-emitting element controlled based on the control information; and provide information regarding the skin condition of the user using the at least one image.

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.

The present disclosure relates to the field of 3D images, and discloses a display control method for a multi-viewpoint 3D display screen, comprising: acquiring identity features of a user; and performing 3D display for the user when the identity features meet conditions. The method can conduct authentication about 3D display for the user, thereby solving a problem of a single 3D display mode, and improving flexibility of 3D display mode. The present disclosure further discloses a multi-viewpoint 3D display device, a computer-readable storage medium, and a computer program product.

A method for synchronizing an action of a target object with source audio is provided. Facial parameter conversion is performed on an audio parameter of the source audio at different time periods to obtain source parameter information of the source audio at the respective time periods. Parameter extraction is performed on a target video that includes the target object to obtain target parameter information of the target video. Image reconstruction is performed on the target object in the target video based on the source parameter information of the source audio and the target parameter information of the target video, to obtain a reconstructed image. Further, a synthetic video is generated based on the reconstructed image, the synthetic video including the target object, and the action of the target object being synchronized with the source audio.

A method and an apparatus for early warning of climbing behaviors, an electronic device, and a storage medium are disclosed. The method includes: acquiring video image data including a monitored target and at least one object (11); acquiring behavior information of the at least one object when it is determined that the at least one object enters a target area corresponding to the monitored target (12); marking video frames in which the at least one object is included when it is determined that the behavior information indicates that the at least one object climbs the monitored target (13). By marking the video frames in the video image data, the behavior of the object climbing the monitored target can be found in time, and the management efficiency can be improved.

There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

An electronic device includes a display; a camera; a first light emitting module, wherein each of the camera and the first light emitting module comprises a first type polarizing filter; a second light emitting module including a second type polarizing filter that is different from the first type polarizing filter; and at least one processor configured to: obtain a first image by using the camera, based on a first light output from the first light emitting module and a second light output from the second light emitting module; identify at least one feature point in the first image; and control the display to display the first image and information related to the at least one feature point.

A facial verification method includes separating a query face image into color channel images of different color channels, obtaining a multi-color channel target face image with a reduced shading of the query face image based on a smoothed image and a gradient image of each of the color channel images, extracting a face feature from the multi-color channel target face image, and determining whether face verification is successful based on the extracted face feature.