The present application relates to a method of acquiring a side image for analyzing the degree of ocular proptosis. According to an embodiment, an image acquisition method is provided which is including: acquiring a front image of the subject's face while guidance is

Oven to satisfy a first photographing condition; generating panorama guidance on the basis of position information of a first point and a second point extracted from the front image; providing guidance on movement of a photographing device to acquire a preview image corresponding to the panorama guidance; and acquiring a side image of the subject's face while guidance is given to satisfy a second photographing condition. The first captured image shows iris areas of the subject, and the second captured image shows an outer canthus and a cornea of one of the subject's eyes.

Systems and techniques described herein relate to techniques for improving image detection. In some examples, aspects relate to systems and techniques for improving image detection by performing tracking of objects within captured image frames. A process can include obtaining, from an image capture device, a first image frame including an object. The process can further include determining, using an object detector, an object validation score associated with detection of the object in the first image frame, and determining the object validation score is less than a validation threshold. Based on the object validation score being less than the validation threshold, the process can include tracking the object for one or more image frames received subsequent to the first image frame.

When a first user makes a video call with a second user of the other side by using the video call function, a first state is set as a state in which the enclosure is flatly placed on a first surface of an object, and in which a face of the first user is included within a range of an angle of view AV1 of the front camera C1. In the first state, the mobile information terminal 1 detects a first region including the face of the first user from a wide angle image that is captured by the front camera C1, trims a first image corresponding to the first region, creates a transmission image to be transmitted to a terminal of the other side on the basis of the first image, and transmits the transmission image to the terminal of the other side.

A display apparatus according to the present invention, includes: a display panel; a display optical system for looking at the display panel; an image sensor for capturing an eye of an user looking at the display panel, the image sensor having a rectangular imaging plane; and an imaging optical system for forming an optical image of the eye on the imaging plane, wherein the imaging optical system has an optical axis that is nonparallel to an optical axis of the display optical system, and a projected line of the optical axis of the display optical system on the imaging plane is substantially parallel to a long side of the imaging plane.

In some examples, an electronic device comprises an image sensor and a processor. The processor is to detect a feature of a frame of a video received via the image sensor, determine whether the feature indicates an object of interest, and, responsive to a determination that the feature indicates the object of interest, limit a first field of view of the image sensor to the object of interest and overlay the first field of view with a second field of view. The second field of view is unlimited.

There is provided a system for performing ambient light image correction. The system comprises a light source, a rolling shutter imaging unit configured to capture a plurality of images of the object at an exposure time shorter than the wave period of the pulsed illumination from the light source, and a control unit configured to generate a first composite image comprising a plurality of bright bands from the plurality of captured images by combining sections from the plurality of captured images which correspond to bright bands, generate a second composite image comprising a plurality of dark bands from the plurality of captured images by combining sections from the plurality of captured images which correspond to dark bands, and generate an ambient light corrected image based on a difference in pixel information between the first composite image and the second composite image.

An imaging apparatus includes: an image sensor that captures a subject image to generate image data; a first depth measurer that acquires first depth information indicating a depth at a first spatial resolution, the depth showing a distance between the imaging apparatus and a subject in an image indicated by the image data; a second depth measurer that acquires second depth information indicating the depth in the image at a second spatial resolution different from the first spatial resolution; and a controller that acquires third depth information indicating the depth at the first or second spatial resolution for each region of different regions in the image, based on the first depth information and the second depth information.

Systems and methods are provided for determining faces and bodies of people in an image by adaptively scaling images and by iteratively using a deep neural network for inferencing. A camera captures an image including faces and bodies of people. A face/body determiner determines faces and bodies of people appearing in the image by resizing the image into a predetermined pixel dimension as input to the deep neural network. A region cropper determines a crop region associated with a low level of confidence in detecting faces and bodies that are too small to determine with an acceptable level of confidence. The region cropper resizes the crop region into the predetermined pixel dimension as input to the deep neural network. The face and body determiner determines other faces and bodies appearing in the resized crop region. An aggregator aggregates locations of the determined faces and bodies in the image.

Systems and methods are provided for determining faces and bodies of people in an image by adaptively scaling images and by iteratively using a deep neural network for inferencing. A camera captures an image including faces and bodies of people. A face/body determiner determines faces and bodies of people appearing in the image by resizing the image into a predetermined pixel dimension as input to the deep neural network. A region cropper determines a crop region associated with a low level of confidence in detecting faces and bodies that are too small to determine with an acceptable level of confidence. The region cropper resizes the crop region into the predetermined pixel dimension as input to the deep neural network. The face and body determiner determines other faces and bodies appearing in the resized crop region. An aggregator aggregates locations of the determined faces and bodies in the image.

This application discloses an image content removal method, and relates to the field of computer vision. The method includes: enabling a camera application; displaying a photographing preview interface of the camera application; obtaining a first preview picture and a first reference frame picture that are captured by a camera; determining a first object in the first preview picture as a to-be-removed object; and determining to-be-filled content in the first preview picture based on the first reference frame picture, where the to-be-filled content is image content that is of a second object and that is shielded by the first object in the first preview picture. The terminal generates a first restored picture based on the to-be-filled content and the first preview picture. In this way, image content that a user does not want in a picture or a video shot by the user can be removed.