Provided is a user equipment for controlling a drone. The user equipment analyzes an original video to control the drone to photograph a reproduction video giving a feeling identical to or similar to the original video. An electronic device may be connected to an artificial intelligence module, a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G service, and the like.

An electronic apparatus includes: control means for performing control to record, in recording means, characteristic data on a line-of-sight; authentication means for authenticating a user; and detection means for detecting, in a case where characteristic data on a line-of-sight of the authenticated user is recorded in the recording means, a line-of-sight of the user by using the recorded characteristic data on the line-of-sight.

Systems, methods, and non-transitory media are provided for adjusting camera settings based on event data. An example method can include obtaining, via an image capture device of a mobile device, an image depicting at least a portion of an environment; determining a match between one or more visual features extracted from the image and one or more visual features associated with a keyframe; and based on the match, adjusting one or more settings of the image capture device.

Techniques for audio tagging of an object of interest are provided. An object of interest within a field of view of a first video camera may be identified at a first time. At least one audio tag representing a first sound created by the object of interest may be generated and associated with the object of interest. At a second time later than the first and at a second video camera, a second sound generated by an unidentified object that is not in the field of view of the second video camera may be detected. An audio tag representing the second tag may be generated. It may be determined that the object of interest and the unidentified object of interest are the same when the audio tag representing the first sound and the second sound are the same.

Techniques for audio tagging of an object of interest are provided. An object of interest within a field of view of a first video camera may be identified at a first time. At least one audio tag representing a first sound created by the object of interest may be generated and associated with the object of interest. At a second time later than the first and at a second video camera, a second sound generated by an unidentified object that is not in the field of view of the second video camera may be detected. An audio tag representing the second tag may be generated. It may be determined that the object of interest and the unidentified object of interest are the same when the audio tag representing the first sound and the second sound are the same.

The present application discloses an imaging system for detecting human-object interaction and a method for detecting human-object interaction thereof. The imaging system includes an event sensor, an image sensor, and a controller. The event sensor is configured obtain an event data set of the targeted scene according to variations of light intensity sensed by pixels of the event sensor when an event occurs in the targeted scene. The image sensor is configured capture a visual image of the targeted scene. The controller is configured to detect human according to the event data set, trigger the image sensor to capture the visual image when the human is detected, and detect the human-object interaction in the targeted scene according to the visual image and a series of event data sets obtained by the event sensor during the event.

The present application discloses an imaging system for detecting human-object interaction and a method for detecting human-object interaction thereof. The imaging system includes an event sensor, an image sensor, and a controller. The event sensor is configured obtain an event data set of the targeted scene according to variations of light intensity sensed by pixels of the event sensor when an event occurs in the targeted scene. The image sensor is configured capture a visual image of the targeted scene. The controller is configured to detect human according to the event data set, trigger the image sensor to capture the visual image when the human is detected, and detect the human-object interaction in the targeted scene according to the visual image and a series of event data sets obtained by the event sensor during the event.

A control apparatus including an extraction unit configured to extract a subject from an image captured by an image capturing apparatus, an estimation unit configured to estimate a skeleton of the subject extracted by the extraction unit and a control unit configured to control an angle of view of the image capturing apparatus based on a result of the estimation by the estimation unit.

Various client devices include displays and one or more image capture devices configured to capture video data. Different users of an online system may authorize client devices to exchange information captured by their respective image capture devices. Additionally, a client device modifies captured video data based on users identified in the video data. For example, the client device changes parameters of the image capture device to more prominently display a user identified in the video data and may further change parameters of the image capture device based on gestures or movement of the user identified in the video data. The client device may apply multiple models to captured video data to modify the captured video data or subsequent capturing of video data by the image capture device.

Systems and techniques are provided for processing image data. According to some aspects, a process can include obtaining a frame captured using an image sensor of a device. The process can include detecting an orientation of the device using a position sensor. The process can further include determining, based on the orientation, a transform to be applied to a region of interest in the frame. The process can include applying the transform to the region of interest. The process can further include providing the transformed region of interest to the object detection algorithm.