Apparatuses, methods, systems, and program products are disclosed for dynamic field of view selection in video. An apparatus includes a processor and memory that stores code executable by the processor to capture a 360-degree video using a 360-degree camera system, detect a direction that a user is looking within the 360-degree video captured using the 360-degree camera system, and set a field of view for the 360-degree video based on the detected direction that the user is looking.

An electronic device includes a memory configured to store instructions, and a processor configured to execute the instructions to configure the processor to obtain a first heat map feature and a first coordinate value feature based on a face image, and detect a face key point based on the first heat map feature and the first coordinate value feature.

There is a need to accurately and dynamically evaluate an individual's risk associated with the transmission or contraction of a disease. This need can be addressed, for example, by generation of a real-time or near real-time predicted disease score for an associated user. In one example, a method includes receiving a video stream data object depicting a visual representation of a target user; processing the video stream data object to generate a protective covering indication with respect to the target user; processing the video stream data object to generate a spatial proximity determination score with respect to the target user; processing the protective covering indication and spatial proximity determination score to generate a predicted disease score associated with the target user; and providing an augmented reality video stream data object configured to depict the visual representation of the target user and the predicted disease score.

Techniques for changing the presentation of information on a user interface based on presence are described. In an example, a computer system determines, based on an image sensor associated with the system, a first presence of a first user relative to a computing device. The computer system also determines an identifier of the first user. The identifier is associated with operating the computing device. The operating comprises a presentation of the user interface by the computing device. The computer system also determines, based on the image sensor, a second presence of a second person relative to the computing device. The computer system causes an update to the user interface based on the second presence.

Among other things, embodiments of the present disclosure improve the functionality of electronic messaging software and systems by providing a customized display of avatars corresponding to users exchanging electronic communications, such as short message service (SMS) or multimedia service (MMS) texts and emails. The appearance of the displayed avatars may be dynamically altered based on the actions taken by the users, as well as based on the content of the messages between the users or information from other sources.

A real-time video enhancement method performed at a terminal includes: obtaining an average luminance of a current frame of an image; in accordance with a determination that the average luminance is less than the luminance threshold: obtaining a pixel range of an area of interest of the current frame; determining a local enhancement curve of the current frame according to the pixel range of the area of interest of the current frame; determining a first enhancement curve corresponding to the current frame according to the average luminance of the current frame; determining a second enhancement curve of the current frame according to the local enhancement curve of the current frame and the first enhancement curve of the current frame; and adjusting the current frame according to the second enhancement curve.

Face model matrix training method, apparatus, and storage medium are provided. The method includes: obtaining a face image library, the face image library including k groups of face images, and each group of face images including at least one face image of at least one person, k>2, and k being an integer; separately parsing each group of the k groups of face images, and calculating a first matrix and a second matrix according to parsing results, the first matrix being an intra-group covariance matrix of facial features of each group of face images, and the second matrix being an inter-group covariance matrix of facial features of the k groups of face images; and training face model matrices according to the first matrix and the second matrix.

A system for quantifying viewer engagement with a video playing on a display includes at least one camera to acquire image data of a viewing area in front of the display. A microphone acquires audio data emitted by a speaker coupled to the display. The system also includes a memory to store processor-executable instructions and a processor. Upon execution of the processor-executable instructions, the processor receives the image data and the audio data and determines an identity of the video displayed on the display based on the audio data. The processor also estimates a first number of people present in the viewing area and a second number of people engaged with the video. The processor further quantifies the viewer engagement of the video based on the first number of people and the second number of people.

A method of generating one or more new digital images using an original digitally-acquired image including a selected image feature includes identifying within a digital image acquisition device one or more groups of pixels that correspond to the selected image feature based on information from one or more preview images. A portion of the original image is selected that includes the one or more groups of pixels. The technique includes automatically generating values of pixels of one or more new images based on the selected portion in a manner which includes the selected image feature within the one or more new images.

A face detecting and tracking method includes: acquiring an image and performing a face detection to determine one or more face boxes of each acquired image; performing a detection error removing process to the image of current frame, and saving one of the one or more face boxes of the processed image of current frame as a first face box; and determining a tracking box of the image of current frame based an the first face box and a tracked face box, and tracking the face in the tracking box of the image of current frame.