The present disclosure may relate to systems and methods for camera synchronization. A method may include determining a frequency difference between a first frequency of a first camera and a second frequency of a second camera. The method may also include synchronizing the second frequency of the second camera to the first frequency of the first camera based on the frequency difference. The method may further include directing the first camera and the second camera to execute camera operations under synchronized frequency.

To transmit ultra-high-definition image data with high frame rate along with preferable backward compatibility on the reception side.

Ultra-high-definition image data with high frame rate is processed to obtain image data in a base format for obtaining a high-definition image with base frame rate, image data in a first extension format for obtaining an ultra-high-definition image with base frame rate, and image data in a second extension format for obtaining an ultra-high-definition image with high frame rate. A base video stream including encoded image data of the image data in the base format, and two or one extended video stream including encoded image data of the image data in the first extension format and encoded image data of the image data in the second extension format are generated. A container in a predetermined format including the base stream and the extended video streams is transmitted.

To transmit ultra-high-definition image data with high frame rate along with preferable backward compatibility on the reception side.

Ultra-high-definition image data with high frame rate is processed to obtain image data in a base format for obtaining a high-definition image with base frame rate, image data in a first extension format for obtaining an ultra-high-definition image with base frame rate, and image data in a second extension format for obtaining an ultra-high-definition image with high frame rate. A base video stream including encoded image data of the image data in the base format, and two or one extended video stream including encoded image data of the image data in the first extension format and encoded image data of the image data in the second extension format are generated. A container in a predetermined format including the base stream and the extended video streams is transmitted.

Tactile vibration signals are transferred favorably in synchronization with audio signals. Transfer signals for respective blocks each including a plurality of frames are sequentially transmitted to a receiver side via a predetermined transfer line. The transfer signals include a predetermined number of channels of audio signals and a predetermined number of channels of tactile vibration signals. For example, the tactile vibration signals are generated on the basis of media signals associated with the audio signals. For example, configuration information of the predetermined number of channels of audio signals and the predetermined number of channels of tactile vibration signals is added to the transfer signals.

Tactile vibration signals are transferred favorably in synchronization with audio signals. Transfer signals for respective blocks each including a plurality of frames are sequentially transmitted to a receiver side via a predetermined transfer line. The transfer signals include a predetermined number of channels of audio signals and a predetermined number of channels of tactile vibration signals. For example, the tactile vibration signals are generated on the basis of media signals associated with the audio signals. For example, configuration information of the predetermined number of channels of audio signals and the predetermined number of channels of tactile vibration signals is added to the transfer signals.

A system and method for lossy image and video compression and transmission that utilizes a neural network as a function to map a known noise image to a desired or target image, allowing the transfer only of hyperparameters of the function instead of a compressed version of the image itself. This allows the recreation of a high-quality approximation of the desired image by any system receiving the hyperparameters, provided that the receiving system possesses the same noise image and a similar neural network. The amount of data required to transfer an image of a given quality is dramatically reduced versus existing image compression technology. Being that video is simply a series of images, the application of this image compression system and method allows the transfer of video content at rates greater than existing technologies in relation to the same image quality.

A system and method for lossy image and video compression and transmission that utilizes a neural network as a function to map a known noise image to a desired or target image, allowing the transfer only of hyperparameters of the function instead of a compressed version of the image itself. This allows the recreation of a high-quality approximation of the desired image by any system receiving the hyperparameters, provided that the receiving system possesses the same noise image and a similar neural network. The amount of data required to transfer an image of a given quality is dramatically reduced versus existing image compression technology. Being that video is simply a series of images, the application of this image compression system and method allows the transfer of video content at rates greater than existing technologies in relation to the same image quality.

Systems, methods, and software for operating an unmanned aerial vehicle (UAV) having one or more camera sensors. A method includes capturing a video stream using the camera sensor(s) of the UAV. The method includes determining a capability of a ground station communicably coupled to the UAV to annotate the video stream. In response to determining that the ground station is capable to annotate the video stream, the method includes transmitting the video stream to the ground station without annotations. Alternatively, in response to determining that the ground station is incapable to annotate the video stream, drawing annotations on the video stream to generate an annotated video stream, and transmitting the annotated video stream to the ground station. Embodiments of the present technology provide enhanced interoperability between UAVs and different types of ground stations to improve streamlining and quality of user experiences as compared to conventional systems and techniques.

Systems, methods, and software for operating an unmanned aerial vehicle (UAV) having one or more camera sensors. A method includes capturing a video stream using the camera sensor(s) of the UAV. The method includes determining a capability of a ground station communicably coupled to the UAV to annotate the video stream. In response to determining that the ground station is capable to annotate the video stream, the method includes transmitting the video stream to the ground station without annotations. Alternatively, in response to determining that the ground station is incapable to annotate the video stream, drawing annotations on the video stream to generate an annotated video stream, and transmitting the annotated video stream to the ground station. Embodiments of the present technology provide enhanced interoperability between UAVs and different types of ground stations to improve streamlining and quality of user experiences as compared to conventional systems and techniques.

Provided is a sensor data processing apparatus and method for autonomous driving. The sensor data processing apparatus for autonomous driving includes a receiver configured to receive a plurality of pieces of sensor data from a plurality of sensors, and a processor configured to obtain information related to the plurality of pieces of sensor data based on a generation time point of the plurality of pieces of sensor data, generate an event indicating an update of a synchronization data group and the plurality of pieces of sensor data based on the information, and transmit synchronized sensor data to a client based on the synchronization data group and the event.