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    Neural network for video editing
    41.
    发明授权
    Neural network for video editing 有权
    用于视频编辑的神经网络

    公开(公告)号：US09456174B2

    公开(公告)日：2016-09-27

    申请号：US14600177

    申请日：2015-01-20

    Applicant: H4 Engineering, Inc.

    Inventor： Christopher T. Boyle ,  Alexander G. Sammons ,  Scott K. Taylor

    IPC: H04N5/93 ,  H04N5/91 ,  G11B27/034 ,  H04N5/765 ,  H04N21/00 ,  H04N9/82 ,  H04N21/218

    CPC classification number: H04N5/91 ,  G11B27/034 ,  G11B27/11 ,  H04N5/765 ,  H04N9/8205 ,  H04N21/00 ,  H04N21/21805

    Abstract: An automated video editing system uses user inputs and metadata combined with machine learning technology to gradually improve editing techniques as more footage is edited. The system is designed to work primarily with a network of automated video recording systems that use cooperative tracking methods. The system is also designed to improve tracking algorithms used in cooperative tracking and to enable systems to begin using image recognition based tracking when the results of machine learning are utilized.

    Abstract translation: 自动视频编辑系统使用用户输入和元数据结合机器学习技术逐渐改进编辑技术，因为更多的素材被编辑。 该系统主要用于使用协作跟踪方法的自动化录像系统网络。 该系统还被设计为改进在协同跟踪中使用的跟踪算法，并且当利用机器学习的结果时，使得系统能够开始使用基于图像识别的跟踪。

    Portable video recording system with automatic camera orienting and velocity regulation of the orienting for recording high quality video of a freely moving subject
    43.
    发明授权
    Portable video recording system with automatic camera orienting and velocity regulation of the orienting for recording high quality video of a freely moving subject 有权
    便携式录像系统，具有自动摄像机定向和速度调节方向，用于录制自由移动物体的高品质视频

    公开(公告)号：US09253376B2

    公开(公告)日：2016-02-02

    申请号：US14223803

    申请日：2014-03-24

    Applicant: H4 Engineering, Inc.

    Inventor： Christopher T. Boyle ,  Scott K. Taylor ,  Alexander G. Sammons ,  John T. O'Callaghan ,  Denes Marton

    IPC: H04N5/232 ,  H04N5/222 ,  G06F3/033

    CPC classification number: H04N5/222 ,  G06F3/011 ,  G06F3/033 ,  H04N5/23203 ,  H04N5/23258

    Abstract: This invention relates to the automatic pointing of a pointing device, such as a camera, without the assistance of a person who operates the camera. Systems and methods are disclosed wherein the system is substantially stationary during recording but is portable to the venue of recording. For the purpose of recording, the camera turns automatically to optically follow the person, animal, or object that is being recorded. The present invention provides for high quality video recording; the high quality video recording here refers to features of the inventive systems and methods that provide for smooth camera motion necessary to take enjoyable videos for personal or for commercial use. This invention provides a portable system that automatically records videos from the vantage point of a sports fan, of a spectator or of a competition judge.

    Abstract translation: 本发明涉及指示设备（例如相机）的自动指向，而不需要操作相机的人的帮助。 公开了系统和方法，其中系统在记录期间基本静止，但是可移动到记录场所。 为了录制的目的，相机自动旋转以光学地跟随正在记录的人物，动物或物体。 本发明提供高质量的视频记录; 这里的高品质视频记录是指本发明的系统和方法的特征，其提供用于为个人或商业用途拍摄愉快的视频所需的平滑相机运动。 本发明提供了一种便携式系统，其自动记录来自体育迷，观众或竞赛法官的有利位置的视频。

    NEURAL NETWORK FOR VIDEO EDITING
    44.
    发明申请
    NEURAL NETWORK FOR VIDEO EDITING 有权
    神经网络视频编辑

    公开(公告)号：US20150208023A1

    公开(公告)日：2015-07-23

    申请号：US14600177

    申请日：2015-01-20

    Applicant: H4 Engineering, Inc.

    Inventor： Christopher T. Boyle ,  Alexander G. Sammons ,  Scott K. Taylor

    IPC: H04N5/91 ,  G11B27/034 ,  H04N5/765

    CPC classification number: H04N5/91 ,  G11B27/034 ,  G11B27/11 ,  H04N5/765 ,  H04N9/8205 ,  H04N21/00 ,  H04N21/21805

    Abstract: An automated video editing system uses user inputs and metadata combined with machine learning technology to gradually improve editing techniques as more footage is edited. The system is designed to work primarily with a network of automated video recording systems that use cooperative tracking methods. The system is also designed to improve tracking algorithms used in cooperative tracking and to enable systems to begin using image recognition based tracking when the results of machine learning are utilized.

    Abstract translation: 自动视频编辑系统使用用户输入和元数据结合机器学习技术逐渐改进编辑技术，因为更多的素材被编辑。 该系统主要用于使用协作跟踪方法的自动化录像系统网络。 该系统还被设计为改进在协同跟踪中使用的跟踪算法，并且当利用机器学习的结果时，使得系统能够开始使用基于图像识别的跟踪。

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