H04N19/166

MACHINE LEARNING OF ENCODING PARAMETERS FOR A NETWORK USING A VIDEO ENCODER

In various examples, machine learning of encoding parameter values for a network is performed using a video encoder. Feedback associated with streaming video encoded by a video encoder over a network may be applied to an MLM(s). Using such feedback, the MLM(s) may predict a value(s) of an encoding parameter(s). The video encoder may then use the value to encode subsequent video data for the streaming. By using the video encoder in training, the MLM(s) may learn based on actual encoded parameter values of the video encoder. The MLM(s) may be trained via reinforcement learning based on video encoded by the video encoder. A rewards metric(s) may be used to train the MLM(s) using data generated or applied to the physical network in which the MLM(s) is to be deployed and/or a simulation thereof. Penalty metric(s) (e.g., the quantity of dropped frames) may also be used to train the MLM(s).

MACHINE LEARNING OF ENCODING PARAMETERS FOR A NETWORK USING A VIDEO ENCODER

In various examples, machine learning of encoding parameter values for a network is performed using a video encoder. Feedback associated with streaming video encoded by a video encoder over a network may be applied to an MLM(s). Using such feedback, the MLM(s) may predict a value(s) of an encoding parameter(s). The video encoder may then use the value to encode subsequent video data for the streaming. By using the video encoder in training, the MLM(s) may learn based on actual encoded parameter values of the video encoder. The MLM(s) may be trained via reinforcement learning based on video encoded by the video encoder. A rewards metric(s) may be used to train the MLM(s) using data generated or applied to the physical network in which the MLM(s) is to be deployed and/or a simulation thereof. Penalty metric(s) (e.g., the quantity of dropped frames) may also be used to train the MLM(s).

Battery efficient wireless network connection and registration for a low-power device

A client device is configured to communicate with an access point over a wireless network, exchanging data with the access point over a selected communication channel. The client device stores an identifier of the selected communication channel. After the wireless connection to the access point has ended, the client device initiates a process to reconnect to the access point over the selected communication channel using the stored identifier.

Battery efficient wireless network connection and registration for a low-power device

A client device is configured to communicate with an access point over a wireless network, exchanging data with the access point over a selected communication channel. The client device stores an identifier of the selected communication channel. After the wireless connection to the access point has ended, the client device initiates a process to reconnect to the access point over the selected communication channel using the stored identifier.

IMAGE TRANSMISSION DEVICE, IMAGE RECEPTION DEVICE AND COMPUTER READABLE MEDIUM

An image transmission device (100) includes a compression unit (16) to generate first compression images (5) which are obtained by irreversibly compressing divided images, and to generate second compression images (6) which are obtained by reversibly compressing each of the first compression images (5), a decompression unit (17) to decompress each of the first compression images (5) as decompression images (7), a division sum image generation unit (12) to generate a division sum image (imgSUM), an error sum image generation unit (13) to generate an error sum image (ΔimgSUM), a judgment unit (14) to generate judgment data (Dj), and a transmission unit (15) to transmit the second compression images (6), the division sum image (imgSUM), the error sum image (ΔimgSUM) and the judgment data (Dj).

IMAGE TRANSMISSION DEVICE, IMAGE RECEPTION DEVICE AND COMPUTER READABLE MEDIUM

An image transmission device (100) includes a compression unit (16) to generate first compression images (5) which are obtained by irreversibly compressing divided images, and to generate second compression images (6) which are obtained by reversibly compressing each of the first compression images (5), a decompression unit (17) to decompress each of the first compression images (5) as decompression images (7), a division sum image generation unit (12) to generate a division sum image (imgSUM), an error sum image generation unit (13) to generate an error sum image (ΔimgSUM), a judgment unit (14) to generate judgment data (Dj), and a transmission unit (15) to transmit the second compression images (6), the division sum image (imgSUM), the error sum image (ΔimgSUM) and the judgment data (Dj).

System and method for automatic encoder adjustment based on transport data

A system and method for transmission of a video stream are provided. The system may include: an encoder adapted to generate a video stream comprising a plurality of encoded frames, encoded according to at least one encoding parameter; a comparator in communication with the encoder, the comparator adapted to compare encoded frames of the plurality of encoded frames with input frames to determine a fitness metric reflective of visual quality of the encoded frames; and a controller in communication with the comparator, the controller adapted to adjust the at least one encoding parameter based on the fitness metric.

System and method for automatic encoder adjustment based on transport data

A system and method for transmission of a video stream are provided. The system may include: an encoder adapted to generate a video stream comprising a plurality of encoded frames, encoded according to at least one encoding parameter; a comparator in communication with the encoder, the comparator adapted to compare encoded frames of the plurality of encoded frames with input frames to determine a fitness metric reflective of visual quality of the encoded frames; and a controller in communication with the comparator, the controller adapted to adjust the at least one encoding parameter based on the fitness metric.

Mesh-based home security system

A network management system manages the operation of a home security system in a communication network, such as a mesh network. The home security system can include multiple components such as a camera, a lighting device, a security alarm, a doorbell switch and doorbell chime, and a fingerprint sensor, which connect with the communication network to perform various operations. The network management system monitors environmental parameters of the communication network, such as parameters associated with the access points and components of the home security system, determines an access point to which a component of the home security system is to be connected for efficient operation of the home security system, and connects the component to the communication network via the determined access point.

Mesh-based home security system

A network management system manages the operation of a home security system in a communication network, such as a mesh network. The home security system can include multiple components such as a camera, a lighting device, a security alarm, a doorbell switch and doorbell chime, and a fingerprint sensor, which connect with the communication network to perform various operations. The network management system monitors environmental parameters of the communication network, such as parameters associated with the access points and components of the home security system, determines an access point to which a component of the home security system is to be connected for efficient operation of the home security system, and connects the component to the communication network via the determined access point.