A system and method are provided for performing operations comprising: receiving one or more images from an image capture device of a medical treatment location; applying a trained machine learning model to the one or more images to detect presence of a patient in the medical treatment location, the trained machine learning model being trained to establish a relationship between one or more features of images of the medical treatment location and patient presence; generating context assessment for the medical treatment location based on the detected presence of the patient; and transmitting, over a network, the context assessment for presentation on a user interface of a client device.

A distance measurement accuracy is improved without increasing power consumption of an image processing apparatus that performs distance-measuring processing. In one embodiment, an image processing apparatus for calculating distance information on an image has a reliability calculation unit 113 configured to calculate reliability in accordance with contrast for each pixel of the image and a distance calculation unit 116 configured to calculate distance information on each of the pixels based on reliability of each of the pixels. The distance calculation unit 116 calculates the distance information about a second pixel group whose reliability is lower than that of a first pixel group by using a collation area whose size is larger than a predetermined size in a range in which an amount of calculation in a case where a collation area of the predetermined size is used for all the pixels of the image is not exceeded.

An image capturing apparatus including a mounting part capable of attaching/detaching a device capable of at least storing a captured image is provided. The image capturing apparatus obtains, if a device mounted in the mounting part has a function of executing image analysis processing for a part or a whole of an image captured by the image capturing apparatus, a processing time that is a time from a predetermined timing associated with a start of the image analysis processing to completion of the processing, if the device is caused to start executing the image analysis processing, obtains a result of the image analysis processing by accessing the device after an elapse of the processing time from the predetermined timing associated with the start.

Implementations set forth herein relate to an automated assistant that can control a camera according to one or more conditions specified by a user. A condition can be satisfied when, for example, the automated assistant detects a particular environment feature is apparent. In this way, the user can rely on the automated assistant to identify and capture certain moments without necessarily requiring the user to constantly monitor a viewing window of the camera. In some implementations, a condition for the automated assistant to capture media data can be based on application data and/or other contextual data that is associated with the automated assistant. For instance, a relationship between content in a camera viewing window and other content of an application interface can be a condition upon which the automated assistant captures certain media data using a camera.

An image capturing device may capture image data for processing to form an image. The image capturing device may perform a hashing procedure on the image data, wherein performing the hashing procedure generates a hash value of the image data. The image capturing device may provide, to an image authentication device, the hash value of the image data, wherein the hash value of the image data is to be used by the image authentication device to validate the image based on a request to authenticate the image received from a receiving device. The image capturing device may process the image data to form the image for display to a user. The image capturing device may provide, after providing the hash value of the image data to the image authentication device, the image for display to the user.

An image capturing method and apparatus, an electronic photography device and a computer-readable storage medium are provided. The image capturing method includes: in a snapshot mode, performing image acquisition at a first frame rate and buffering an acquired first captured image; in a live mode, acquiring a second captured image at a second frame rate, where the second frame rate is less than the first frame rate; and processing the buffered first captured image and the second captured image at the second frame rate.

An imaging device includes an image sensor configured to capture a subject image at a predetermined frame rate and generate imaging data for each frame; and a controller configured to control a display to display a captured image corresponding to the imaging data for each frame, wherein first follow-up information can be displayed on the captured image in the display with a frame delay to indicate a result of a first follow-up operation of following a subject on the captured image, and the controller generates second follow-up information that is displayed in a delay period shorter than the frame delay of the first follow-up information to indicate a result of a second follow-up operation different from the first follow-up operation.

Embodiments of systems and methods for intelligent orchestration of video participants in a platform framework are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: process at least a first portion of a video workload using the processor; and in response to a change in context of the IHS, process at least a second portion of the video workload using an offload core.

A method includes capturing, by a camera disposed behind a display panel of an electronic device, an original image through a semi-transparent pixel region of the display panel. The original image includes one or more color components. The method further includes determining, for a plurality of pixel regions of the original image, a point spread function (PSF) for each of the one or more color components. The method further includes performing, for the plurality of pixel regions of the original image, a deconvolution of each of the one or more color components of the original image based at least in part on their respective PSFs. The method thus includes generating a reconstructed image corresponding to the original image based on the deconvolutions of the one or more color components of the plurality of pixel regions of the original image.

An image processing apparatus includes obtaining distance information and subject information with respect to a captured image, specifying, based on the obtained distance information, a first subject region in which images of subjects that exist in a predetermined distance range are distributed in the captured image, specifying, based on the subject information and independently of the obtained distance information, specifying a second subject region that includes a region from which the predetermined subject has been detected in the captured image, and determining a target region for which the image processing is executed with reference to at least one of the first subject region and the second subject region. A subject region varies depending on at least one of an image capture condition of the captured image and a state of the captured image.