Enhanced graphical user interfaces for transcription of audio and video messages is disclosed. Audio data may be transcribed, and the transcription may include emphasized words and/or punctuation corresponding to emphasis of user speech. Additionally, the transcription may be translated into a second language. A message spoken by a user depicted in one or more images of video data may also be transcribed and provided to one or more devices.

An apparatus including an interface and a processor. The interface may be configured to receive pixel data. The processor may be configured to generate a plurality of video frames in response to the pixel data received from the interface, perform computer vision operations to detect objects in the video frames, extract features of the objects in response to characteristics of the objects determined using the computer vision operations, identify a person in the video frames based on the features, detect an event based on the person identified and generate a notification in response to detecting the event and a permission status. The permission status may suppress sending the notification when the permission status for the person identified corresponds to denying the notification and enable sending the notification when the permission status does not correspond to denying the notification.

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.

A lifting hook bias angle monitoring apparatus, a vertical hoisting monitoring apparatus, and a mobile crane. One method is that a lifting hook assembly serially connects connecting plates (b3) provided with hinge connection shafts (b2, b4) at two ends to a movable pulley component (b1) which bears a pulling force and a lifting hook component (b7) which bears a pulling force, and is also provided with a biaxial inclinometer (b9) on a platform surface (b8) of the connecting plates (b3) which is perpendicular to a lifting force line of action of the lifting pulley component, so as to detect a real-time lifting hook bias angle, and accordingly be developed into a mobile crane having a vertical hoisting monitoring function.

A wireless camera network is disclosed. The wireless camera network includes a first camera and one or more other cameras. After an input is received by the first camera, the first camera records images or video, and the first camera wirelessly transmits a start signal to one or more other cameras to also start recording images or video and to also wirelessly transmit the start signal.

A method includes dispatching a drone to a site. The drone includes audio/visual equipment. The method includes logging a plurality of timestamped locations of the drone and receiving, from the audio/visual equipment, site data captured by an on-site operator of the audio/visual equipment. The method includes correlating a portion of the site data with at least one of the timestamped locations of the drone.

A video collection system comprising a body-wearable video camera, a camera dock, and a video collection manager. The camera dock is configured to interface with the body-wearable video camera having a camera-memory element. The camera dock includes a dock-memory element configured to receive and store video data from the camera-memory element. The video collection manager is communicatively coupled with the camera dock. The camera dock sends at least a portion of the video data to the video collection manager.

Disclosed is a system and method for reducing the total latency for transferring a frame from the low latency camera system mounted on an aerial vehicle to the display of the remote controller. The method includes reducing the latency through each of the modules of the system, i.e. through a camera module, an encoder module, a wireless interface transmission, wireless interface receiver module, a decoder module and a display module. To reduce the latency across the modules, methods such as overclocking the image processor, pipelining the frame, squashing the processed frame, using a fast hardware encoder that can perform slice based encoding, tuning the wireless medium using queue sizing, queue flushing, bitrate feedback, physical medium rate feedback, dynamic encoder parameter tuning and wireless radio parameter adjustment, using a fast hardware decoder that can perform slice based decoding and overclocking the display module are used.

According to the present invention there is provided a drone (1) comprising one or more propellers (2) and one or more actuators (3) for actuating said one or more propellers (2) to generating a thrust force which enables the drone (1) to fly; a controller (4) which is configured such that it can control the flight of the drone (1), wherein the controller (4) comprises a memory (6) having stored therein a plurality of predefined sets of positions which define a virtual rail which can be used to guide the flight of the drone (1) so that the drone can avoid collision with an subject; and wherein the controller further comprises a mathematical model (7) of the drone; wherein the controller (4) is configured to control the flight of the drone by performing at least the following steps, (a) approximating lag error based on the position of the drone (1) measured by a sensor (5) and the virtual rail, wherein the lag error is the distance between a point along the virtual rail which is closest to the drone (1) and an estimate of said point along the virtual rail which is closest to the drone (1); (b) approximating a contour error based on the position of the drone (1) as measured by a sensor (5) and the virtual rail, wherein the contour error is the distance between a point along the virtual rail which is closest to the drone (1) and the position of the drone (1); (c) defining a cost function which comprises at least said approximation of the lag error and said approximation of the contour error; (d) minimizing the defined cost function, while also respecting at least limitations of the drone which are defined in said mathematical model, to determine a plurality of control inputs over a predefined time period into the future, and (e) applying the first control input only to the one or more actuators (3). There is further provided a corresponding method for controlling the flight of a drone.

A system including a motorized base unit with a smart device mount for automatically orienting the smart device camera toward a moving target to track the moving target and take pictures or video. The target (e.g., a child playing soccer) wears a tracking tag comprising a GPS chip and transmitter packaged inside an athletic pad. The base unit includes a motorized mast for mounting a smart device. The base unit receives the transmitted GPS data, calculates updated pointing angle and angular velocity for the smart phone based on update location information from the remote tag sensor, calculates the correct angle that the smart phone should be pointed at, translates the new pointing directions to a control signal that turns the mast, which in turn causes the smart device camera to “follow” or track the target.