Abstract: Disclosed in some examples are methods, systems, and machine-readable mediums which customizes application feature settings using ranked clusters from an unsupervised modelling algorithm that clusters similar computing platforms and feature settings templates that map these ranks to feature settings. In some examples, a model may is periodically built using a first set of computing platform properties observed from computing platforms that the application is executing on. These clusters are then ranked using a second set of computing platform properties observed from other computing platforms that the application is executing on and performance data that describes performance of the application on those platforms.

Abstract: Disclosed in some examples are methods, systems, and machine-readable mediums which customizes application feature settings using ranked clusters from an unsupervised modelling algorithm that clusters similar computing platforms and feature settings templates that map these ranks to feature settings. In some examples, a model may is periodically built using a first set of computing platform properties observed from computing platforms that the application is executing on. These clusters are then ranked using a second set of computing platform properties observed from other computing platforms that the application is executing on and performance data that describes performance of the application on those platforms.

Abstract: Techniques are described for low-latency streaming of media content using a lossless protocol. For example, a media stream, comprising encoded video data, can be streamed to a plurality of streaming clients via the lossless protocol. The plurality of streaming clients can be monitored to determine whether any of them have fallen behind in streaming the media stream. When a streaming client falls behind, a portion of video data to be streamed to the streaming client can be selectively dropped based on scalability information and/or long term reference (LTR) frame information. The low-latency streaming can be performed without using per-client quality feedback from the plurality of streaming clients. When streaming using a semi-lossy protocol, a plurality of delivery modes can be used, where each delivery mode is for a different type of encoded video data and provides a different level of reliability.

Abstract: Innovations in adaptive encoding of screen content based on motion type are described. For example, a video encoder system receives a current picture of a video sequence. The video encoder system determines a current motion type for the video sequence and, based at least in part on the current motion type, sets one or more encoding parameters. Then, the video encoder system encodes the current picture according to the encoding parameter(s). The innovations can be used in real-time encoding scenarios when encoding screen content for a screen sharing application, desktop conferencing application, or other application. In some cases, the innovations allow a video encoder system to adapt compression to different characteristics of screen content at different times within the same video sequence.

Abstract: A method and system for managing delivery of a content stream to a plurality of devices participating in an online conference session, including delivering, to each of the devices, the content stream associated with the online conference session at a first signal quality, receiving an indication signal indicating that a first device is to broadcast the content stream, responsive to the indication signal, increasing a signal quality of the content stream delivered to the first device from the first signal quality to a second signal quality, wherein the second signal quality is higher than the first signal quality, delivering the content stream to the first device at the second signal quality, and delivering the content stream to the rest of the devices at the first signal quality or a third signal quality, wherein the third signal quality is lower than the first signal quality.

Abstract: Techniques are described for low-latency streaming of media content using a lossless protocol. For example, a media stream, comprising encoded video data, can be streamed to a plurality of streaming clients via the lossless protocol. The plurality of streaming clients can be monitored to determine whether any of them have fallen behind in streaming the media stream. When a streaming client falls behind, a portion of video data to be streamed to the streaming client can be selectively dropped based on scalability information and/or long term reference (LTR) frame information. The low-latency streaming can be performed without using per-client quality feedback from the plurality of streaming clients. When streaming using a semi-lossy protocol, a plurality of delivery modes can be used, where each delivery mode is for a different type of encoded video data and provides a different level of reliability.

Abstract: Techniques are described for low-latency streaming of media content using a lossless protocol. For example, a media stream, comprising encoded video data, can be streamed to a plurality of streaming clients via the lossless protocol. The plurality of streaming clients can be monitored to determine whether any of them have fallen behind in streaming the media stream. When a streaming client falls behind, a portion of video data to be streamed to the streaming client can be selectively dropped based on scalability information and/or long term reference (LTR) frame information. The low-latency streaming can be performed without using per-client quality feedback from the plurality of streaming clients. When streaming using a semi-lossy protocol, a plurality of delivery modes can be used, where each delivery mode is for a different type of encoded video data and provides a different level of reliability.

Abstract: Innovations in allocation of bit rate between video streams using machine learning are described. For example, a controller of a video encoder system receives first feedback values that indicate results of encoding part of a first video sequence (e.g., screen content). The controller also receives second feedback values that indicate results of encoding part of a second video sequence (e.g., camera video content). A machine learning model accepts, as inputs, the first feedback values and second feedback values. The machine learning model produces, as output, a reallocation parameter. The controller determines a first target bit rate and a second target bit rate using the reallocation parameter. A first video encoder encodes one or more pictures of the first video sequence at the first target bit rate, and a second video encoder encodes one or more pictures of the second video sequence at the second target bit rate.

Abstract: Innovations in adaptive encoding of screen content based on motion type are described. For example, a video encoder system receives a current picture of a video sequence. The video encoder system determines a current motion type for the video sequence and, based at least in part on the current motion type, sets one or more encoding parameters. Then, the video encoder system encodes the current picture according to the encoding parameter(s). The innovations can be used in real-time encoding scenarios when encoding screen content for a screen sharing application, desktop conferencing application, or other application. In some cases, the innovations allow a video encoder system to adapt compression to different characteristics of screen content at different times within the same video sequence.

Abstract: A method and system for managing delivery of a content stream to a plurality of devices participating in an online conference session, including delivering, to each of the devices, the content stream associated with the online conference session at a first signal quality, receiving an indication signal indicating that a first device is to broadcast the content stream, responsive to the indication signal, increasing a signal quality of the content stream delivered to the first device from the first signal quality to a second signal quality, wherein the second signal quality is higher than the first signal quality, delivering the content stream to the first device at the second signal quality, and delivering the content stream to the rest of the devices at the first signal quality or a third signal quality, wherein the third signal quality is lower than the first signal quality.

Abstract: Techniques are described for encapsulating AV1 encoded video data within NAL units. For example, the NAL units can be H.264 or HEVC NAL units. Encapsulation can comprise using a reserved NAL unit type. For example, an open bitstream unit comprising AV1 encoded video data can be encapsulated within a NAL unit using a reserved NAL unit type. The NAL unit can be packetized for delivery to another computing device via a computer network.

Abstract: Techniques are described for encapsulating AV1 encoded video data within NAL units. For example, the NAL units can be H.264 or HEVC NAL units. Encapsulation can comprise using a reserved NAL unit type. For example, an open bitstream unit comprising AV1 encoded video data can be encapsulated within a NAL unit using a reserved NAL unit type. The NAL unit can be packetized for delivery to another computing device via a computer network.

Abstract: Video content is relayed from a transmitting device to a receiving device via a video relay server. The content comprises a plurality of frames. Before encoding, each of the plurality of frames is formed of a respective array of desired image data to be displayed at the receiving device. Filler image data is added to each of the plurality of frames before encoding. Control data is generated, which comprises cropping data indicating that none, or only some, of the filler image data should be cropped out before the plurality of frames is displayed. The encoded video content and the control data is transmitted to the server. At the server, the filler image data is detected automatically; in response, the cropping data is modified to indicate that all of the filler data should be cropped out before displaying the frames.