A method and apparatus for waking up a device, an electronic device, and a storage medium are provided, which are related to fields of image processing and deep learning. The method includes: acquiring an environment image of a surrounding environment of a target device in real time, and recognizing a face region of a user in the environment image; acquiring a plurality of facial landmarks in the face region, and acquiring a left eye image and a right eye image according to the facial landmarks; acquiring a left eye sight classification result and a right eye sight classification result according to the left eye image and the right eye image; and waking up the target device in a case of determining that the user is looking at the target device according to the left eye sight classification result and the right eye sight classification result.

An example method includes causing a light projecting system of a distance sensor to project a three-dimensional pattern of light onto an object, wherein the three-dimensional pattern of light comprises a plurality of points of light that collectively forms the pattern, causing a light receiving system of the distance sensor to acquire an image of the three-dimensional pattern of light projected onto the object, causing the light receiving system to acquire a two-dimensional image of the object, detecting a feature point in the two-dimensional image of the object, identifying an interpolation area for the feature point, and computing three-dimensional coordinates for the feature point by interpolating using three-dimensional coordinates of two points of the plurality of points that are within the interpolation area.

The present disclosure provides a verification system. The verification system is formed with a trusted execution environment, the verification system includes a processor set, and the processor set is configured to: obtain an infrared image to be verified of a target object; determine, in the trusted execution environment, whether the infrared image to be verified matches a pre-stored infrared template; in response to determining that the infrared image to be verified matches the pre-stored infrared template, obtain a depth image to be verified of the target object; and determine, in the trusted execution environment, whether the depth image to be verified matches a pre-stored depth template.

In order to acquire recognition environment information impacting the recognition accuracy of a recognition engine, an information processing device 100 comprises a detection unit 101 and an environment acquisition unit 102. The detection unit 101 detects a marker, which has been disposed within a recognition target zone for the purpose of acquiring information, from an image captured by means of an imaging device which captures images of objects located within the recognition target zone. The environment acquisition unit 102 acquires the recognition environment information based on image information of the detected marker. The recognition environment information is information representing the way in which a recognition target object is reproduced in an image captured by the imaging device when said imaging device captures an image of the recognition target object located within the recognition target zone.

Disclosed is a system and method for obtaining optical properties of skin on a human face through face video analysis. Video of the face is captured, landmarks on the face and tracked, regions-of-interest are defined and tracked using the landmarks, some measurements/optical properties are obtained, the time-based video is transformed into an angular domain, and additional measurements/optical properties are obtained. Such optical properties can be measured using video in real-time or video that has been pre-recorded.

A computer-implemented method for implementing face recognition includes receiving training data including a plurality of augmented images each corresponding to a respective one of a plurality of input images augmented by one of a plurality of variations, splitting a feature embedding generated from the training data into a plurality of sub-embeddings each associated with one of the plurality of variations, associating each of the plurality of sub-embeddings with respective ones of a plurality of confidence values, and applying a plurality of losses including a confidence-aware identification loss and a variation-decorrelation loss to the plurality of sub-embeddings and the plurality of confidence values to improve face recognition performance by learning the plurality of sub-embeddings.

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.

A method and apparatus may be used for performing a scene-based automatic white balance correction. The method may include obtaining an input image. The method may include obtaining a raw image thumbnail. The method may include obtaining an augmented image thumbnail. The method may include computing a histogram from an image thumbnail. The method may include determining a scene classification. The method may include learning a filter. The filter may be learned from one or several different instances of the raw image thumbnail, the augmented image thumbnail, the scene classification, or any combination thereof. The method may include applying the filter to the histogram to determine white balance correction coefficients and obtain a processed image.

The present disclosure relates to systems and methods for selecting a best facial image of a target human face. The methods may include determining whether a candidate facial image is obtained before a time point in a time period threshold, wherein the candidate facial image has a greatest quality score of the target human face among a plurality of facial images of the target human face; in response to a determination that the candidate facial image is obtained before the time point, determining the candidate facial image as the best facial image of the target human face; and storing the best facial image together with a face ID and the greatest quality score of the target human face in a face log.

A method and electronic device for determining relevant signals in radar signal processing. The electronic device includes a radar transceiver, a memory, and a processor. The processor is configured to cause the electronic device to obtain, via the radar transceiver of the electronic device, radar measurements for one or more modes in a set of modes; process the radar measurements to obtain a set of radar images; identify relevant signals in the set of radar images based on signal determination criteria for an application; and perform the application using only the relevant signals.