The various implementations described herein include methods, devices, and systems for detecting motion and persons. In one aspect, a method is performed at a smart home system that includes a video camera, a server system, and a client device. The video camera captures video and audio, and wirelessly communicates, via the server system, the captured data to the client device. The server system: (1) receives and stores the captured data from the video camera; (2) determines whether an event has occurred, including detected motion; (3) in accordance with a determination that the event has occurred, identifies video and audio corresponding to the event; and (4) classifies the event. The client device receives information indicative of the identified events, displays a user interface for reviewing the video and audio stored by the remote server system, and displays the at least one classification for the event.

An imaging support device that supports imaging performed by an imaging apparatus includes an acquisition portion that acquires an in-image shift amount between a predetermined position in a captured image obtained by capturing an imaging region by an imaging element and a position of a target subject image showing a target subject, and a focal length of the imaging apparatus, a derivation portion that derives a movement amount required for moving the position of the target subject image to a specific position by a position adjustment portion which adjusts the position of the target subject image in the captured image, based on the in-image shift amount acquired by the acquisition portion, the focal length acquired by the acquisition portion, and information related to a pixel interval of pixels in the imaging element, and an output portion that outputs the movement amount derived by the derivation portion.

Techniques and systems are provided for generating media content. For example, a server computer can detect a trigger from a device located at a site. The trigger is associated with an event at the site. The server computer can obtain media segments of media captured by a plurality of media capture devices located at the site. At least one of the media segments corresponds to the detected trigger. The server computer can determine one or more quality metrics of a media segment based on a first motion of an object captured in the media segment and/or a second motion of a media capture device used to capture the media segment. A subset of media segments can be selected from the obtained media segments based on quality metrics determined for the obtained media segments. A collection of media segments including the subset of media segments can then be generated.

There is provided a notifying apparatus. A detecting unit detects a motion amount of an object from an image obtained through first shooting, the first shooting being carried out repeatedly at predetermined intervals of time. A converting unit converts the motion amount into a motion blur amount that will arise in second shooting, on the basis of the predetermined intervals of time and an exposure time used in the second shooting. A notifying unit makes a notification of motion blur on the basis of the motion blur amount. The notifying unit changes a form of the notification in accordance with a magnitude of the motion blur amount.

Provided are a device and method that calculate a predicted motion vector corresponding to a type and posture of a tracked subject, and generate a camera control signal necessary for capturing an image of a tracked subject. There are included a predicted subject motion vector calculation unit that detects a tracked subject of a previously designated type from a captured image input from an imaging unit and calculates a predicted motion vector corresponding to a type and posture of the detected tracked subject, and a camera control signal generation unit that generates, on the basis of the predicted motion vector calculated by the predicted subject motion vector calculation unit, a camera control signal for capturing an image of a tracked image of the tracked subject. By using a neural network or the like, the predicted subject motion vector calculation unit executes processing of detecting a tracked subject of a type designated from the captured image by a user, and predicted motion vector calculation processing.

An image stabilization control apparatus includes at least one processor or circuit which functions as an obtaining unit configured to obtain resolving power of an imaging system, a control unit configured to control a correction unit configured to correct an effect of shake acting on an imaging apparatus to which the lens apparatus is attached on the captured image, and a setting unit configured to set responsiveness of the correction unit controlled by the control unit based on the resolving power of the imaging system and an imaging condition, wherein the setting unit is configured to, in a case where the imaging condition satisfies a predetermined condition and the resolving power of the imaging system has a first value, set the responsiveness of the correction unit to be higher than in a case where the resolving power has a second value less than the first value.

A method includes receiving selection of a target within an image captured by an image sensor of a payload and displayed on a user interface of the payload, detecting a deviation of the target from an expected target state within the image, generating, based at least partly on the deviation, a payload control signal including a first angular velocity for rotating the payload about an axis of the carrier to reduce the deviation about the axis in a subsequent image, and generating a base support control signal including a second angular velocity for rotating the payload with respect to the axis. When the first and second angular velocities are received, the carrier is controlled to rotate the payload at a third angular velocity about the axis. The third angular velocity is the first angular velocity, the second angular velocity, or a combination of both.

A portable electronic device with image capturing capabilities automatically or semi-automatically adjusts one or more image capturing parameters based on an input attribute of user engagement with a single-action haptic input mechanism. For example, the duration for which a single-action control button carried on a frame of the device is pressed automatically determines an image stabilization mode for on-board processing of captured image data. In one example, an above-threshold press duration automatically activates a less rigorous image stabilization mode, while button release before expiry of the threshold automatically activates a more rigorous photo stabilization mode.

An image processing apparatus includes a reception unit that receives an image signal acquired by an image sensor, an acceptance unit that accepts operation input made by a user for driving a device carrying the image sensor, a calculation unit that calculates a movement amount of the image sensor in an entire angle of view according to the image signal and the operation input, and a correction processing unit that performs a correction process for an image constructed from the image signal, according to the movement amount.

An electronic device is provided. The electronic device includes at least one processor, and a memory functionally connected to the at least one processor. The memory may store instructions that, when executed, enable the electronic device to obtain a plurality of images, generate a first basic extended image based on first images among the plurality of images, identify at least one first masking area included in the first basic extended image, and generate a first inference image by modifying the at least one first masking area using at least one first inference result, based on the first images and the first basic extended image. An angle of view of the first inference image may be larger than an angle of view of each of the first images.