Interactive virtual display system
    4.
    发明授权
    Interactive virtual display system 有权
    交互式虚拟显示系统

    公开(公告)号:US09323429B2

    公开(公告)日:2016-04-26

    申请号:US14063106

    申请日:2013-10-25

    Abstract: An “Interactive Virtual Display,” as described herein, provides various systems and techniques that facilitate ubiquitous user interaction with both local and remote heterogeneous computing devices. More specifically, the Interactive Virtual Display uses various combinations of small-size programmable hardware and portable or wearable sensors to enable any display surface (e.g., computer display devices, televisions, projected images/video from projection devices, etc.) to act as a thin client for users to interact with a plurality heterogeneous computing devices regardless of where those devices are located relative to the user. The Interactive Virtual Display provides a flexible system architecture that enables communication and collaboration between a plurality of both local and remote heterogeneous computing devices. This communication and collaboration enables a variety of techniques, such as adaptive screen compression, user interface virtualization, real-time gesture detection to improve system performance and overall user experience, etc.

    Abstract translation: 如本文所描述的,“交互式虚拟显示器”提供了促进无处不在的用户与本地和远程异构计算设备交互的各种系统和技术。 更具体地,交互式虚拟显示器使用小尺寸可编程硬件和便携式或可穿戴式传感器的各种组合来实现任何显示表面(例如,计算机显示设备,电视,投影图像/来自投影设备的视频等)作为 瘦客户机,用于用户与多个异构计算设备交互,而不管这些设备相对于用户位于何处。 交互式虚拟显示器提供灵活的系统架构,可实现多个本地和远程异构计算设备之间的通信和协作。 这种通信和协作实现了各种技术,例如自适应屏幕压缩,用户界面虚拟化,实时手势检测,以提高系统性能和整体用户体验等。

    Reinforcement learning based rate control

    公开(公告)号:US12262032B2

    公开(公告)日:2025-03-25

    申请号:US18013240

    申请日:2020-06-30

    Abstract: Implementations of the subject matter described herein provide a solution for rate control based on reinforcement learning. In this solution, an encoding state of a video encoder is determined, the encoding state being associated with encoding of a first video unit by the video encoder. An encoding parameter associated with rate control in the video encoder is determined by a reinforcement learning model and based on the encoding state of the video encoder. A second video unit different from the first video unit is encoded based on the encoding parameter. In this way, it is possible to achieve a better quality of experience (QOE) for real time communication with computation overhead being reduced.

    Cooperative web browsing using multiple devices

    公开(公告)号:US11727079B2

    公开(公告)日:2023-08-15

    申请号:US17189882

    申请日:2021-03-02

    CPC classification number: G06F16/9577

    Abstract: A computer-implemented method for displaying at least a portion of content being displayed on a first device to also be displayed on a second device. The method includes causing content to be displayed on a first device. The method then includes detecting a second device to concurrently display at least a portion of the content being displayed on the first device. A capability of the first device is compared with a capability of the second device. Based on the comparing, the at least the portion of the content is automatically provided to be displayed on the second device.

    REINFORCEMENT LEARNING FOR JITTER BUFFER CONTROL

    公开(公告)号:US20230138038A1

    公开(公告)日:2023-05-04

    申请号:US18091992

    申请日:2022-12-30

    Abstract: Disclosed in some examples are methods, systems, and machine-readable mediums which determine jitter buffer delay by inputting jitter buffer and currently observed network status information to a machine learned model that is trained using a reinforcement learning (RL) method. The model maps these inputs to an action to compress, stretch, or hold the jitter buffer delay, which is used by a recipient computing device to optimize the jitter buffer delay. The model may be trained using a simulator that uses network traces of past real streaming sessions (e.g., communication sessions) of users. By training the model through reinforcement learning, the model learns to make better decisions through reinforcement in the form of reward signals that reflect the performance of each decision.

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