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    On-device machine learning-based network bandwidth prediction to improve adaptive media streaming performance
    13.
    发明授权
    On-device machine learning-based network bandwidth prediction to improve adaptive media streaming performance 有权

    公开(公告)号：US12273253B2

    公开(公告)日：2025-04-08

    申请号：US18184316

    申请日：2023-03-15

    Applicant: Apple Inc.

    Inventor： Soutik Chakraborty ,  John Y. Su ,  Eunhee Lim ,  Jacob A. Baron

    IPC: H04L43/0888 ,  H04L41/16 ,  H04L65/60

    Abstract: A media streaming method is disclosed in which a network environment of a sink device engaged in media streaming is estimated and at least two network throughput estimates are developed. A first network throughput estimate may be estimated from a measurement of network performance and a second network throughput estimate may be developed from a correlation of the estimated network environment to a machine learning model representing network throughput predictions. A final throughput estimate may be developed from the first and second network throughput estimates; and a representation of media content may be selected for retrieval based on the final throughput estimate. The machine learning model of network throughput may be developed over the course of prior media streaming session(s) that are performed by the sink device in which network throughput performance indicators of the streaming session(s) are stored over a predetermined interval and, upon conclusion of the interval, the model of network throughput is constructed according to a machine learning technique. Both the logging network throughput performance indicators and the building of the model of network throughput may be performed solely by the sink device, which preserves confidentiality of data representing consumer behavior during those media streaming sessions.

    IMAGE FETCHING FOR TIMELINE SCRUBBING OF DIGITAL MEDIA
    18.
    发明申请
    IMAGE FETCHING FOR TIMELINE SCRUBBING OF DIGITAL MEDIA 有权
    数字媒体时代滚屏的图像截止

    公开(公告)号：US20160372156A1

    公开(公告)日：2016-12-22

    申请号：US14743955

    申请日：2015-06-18

    Applicant: Apple Inc.

    Inventor： David Alan Pound ,  Roger N. Pantos ,  Christopher L. Oklota ,  David L. Biderman ,  John Y. Su

    IPC: G11B27/30 ,  H04N21/431 ,  H04N21/472 ,  H04N21/482 ,  G06T13/80 ,  G11B27/10

    CPC classification number: G06T13/80 ,  G06T7/564 ,  G06T17/00 ,  G06T2200/08 ,  G06T2207/10028 ,  G11B27/102 ,  G11B27/105 ,  G11B27/3081 ,  G11B27/34 ,  H04N21/4316 ,  H04N21/47217 ,  H04N21/4825

    Abstract: The present disclosure describes systems and techniques relating to generating three dimensional (3D) models from range sensor data. According to an aspect, frames of range scan data captured using one or more three dimensional (3D) sensors are obtained, where the frames correspond to different views of an object or scene; point clouds for the frames are registered with each other by maximizing coherence of projected occluding boundaries of the object or scene within the frames using an optimization algorithm with a cost function that computes pairwise or global contour correspondences; and the registered point clouds are provided for use in 3D modeling of the object or scene. Further, the cost function, which maximizing contour coherence, can be used with more than two point clouds for more than two frames at a time in a global optimization framework.

    Abstract translation: 本公开描述了与从距离传感器数据生成三维（3D）模型有关的系统和技术。 根据一个方面，获得使用一个或多个三维（3D）传感器捕获的范围扫描数据的帧，其中帧对应于对象或场景的不同视图; 使用具有计算成对或全局轮廓对应关系的成本函数的优化算法，通过最大化框架内的对象或场景的投影遮挡边界的相干性来相互注册用于帧的点云; 并且注册的点云被提供用于对象或场景的3D建模。 此外，最大化轮廓一致性的成本函数可以在全局优化框架中一次与两个以上的多个云一起使用。

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