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    Event analysis system
    4.
    发明授权
    Event analysis system 有权
    事件分析系统

    公开(公告)号：US09401178B2

    公开(公告)日：2016-07-26

    申请号：US14801341

    申请日：2015-07-16

    申请人： BLAST MOTION INC.

    发明人： Michael Bentley ,  Ryan Kaps ,  Bhaskar Bose ,  Piyush Gupta ,  Juergen Haas ,  Brian Estrem

    IPC分类号： A63F13/12 ,  G11B27/031 ,  G06K9/00 ,  G08B21/04 ,  G06T7/20 ,  H04N7/18 ,  H04N21/422 ,  A63F13/355 ,  A63F13/212

    CPC分类号： G11B27/031 ,  A63F13/212 ,  A63F13/355 ,  A63F2300/105 ,  A63F2300/69 ,  G06K9/00342 ,  G06K9/00724 ,  G06K9/00751 ,  G06T7/20 ,  G06T2207/30221 ,  G08B21/043 ,  G08B21/0492 ,  H04N7/181 ,  H04N21/42201 ,  H04N21/42202 ,  H04N21/42203

    摘要： Enables event analysis from sensors including environmental, physiological and motion capture sensors. Also enables displaying information based on events recognized using sensor data associated with a user, piece of equipment or based on previous motion analysis data from the user or other user(s) or other sensors. Enables intelligent analysis, synchronization, and transfer of generally concise event videos synchronized with motion data from motion capture sensor(s) coupled with a user or piece of equipment. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Greatly saves storage and increases upload speed by uploading event videos and avoiding upload of non-pertinent portions of large videos. Creates highlight and fail reels filtered by metrics and can sort by metric. Compares motion trajectories of users and objects to optimally efficient trajectories, and to desired trajectories.

    摘要翻译： 实现来自传感器的事件分析，包括环境，生理和运动捕捉传感器。 还能够基于使用与用户，设备相关联的传感器数据识别的事件或者基于来自用户或其他用户或其他传感器的先前运动分析数据来显示信息。 实现与运动捕捉传感器（与用户或设备）耦合的运动数据同步的一般简洁的事件视频的智能分析，同步和传输。 可以创建，传输，获取和存储简洁的事件视频，而无需非事件视频。 存储在数据库中的事件标识事件数据中的趋势，相关性，模型和模式。 通过上传事件视频并避免上传大型视频的非相关部分，大大节省存储空间并提高上传速度。 创建由指标过滤的突出显示和失败卷轴，并可按指标排序。 将用户和对象的运动轨迹与最佳有效的轨迹和所需的轨迹进行比较。

    Initializing an inertial sensor using soft constraints and penalty functions
    5.
    发明授权
    Initializing an inertial sensor using soft constraints and penalty functions 有权
    使用软约束和惩罚功能初始化惯性传感器

    公开(公告)号：US08913134B2

    公开(公告)日：2014-12-16

    申请号：US14258291

    申请日：2014-04-22

    申请人： Blast Motion, Inc.

    发明人： John Goree ,  Bhaskar Bose ,  Piyush Gupta

    IPC分类号： H04N7/18 ,  G01P15/00 ,  A63B15/02 ,  G01P15/02 ,  A63F13/00 ,  G06Q10/08 ,  H04M1/725

    CPC分类号： G01P15/02 ,  A63F13/00 ,  G01C25/005 ,  G06Q10/0833 ,  H04M1/7253 ,  H04M2250/12 ,  H04N7/18

    摘要： An initialization method for an inertial sensor that estimates starting orientation and velocity without requiring the sensor to start at rest or in a well-known location or orientation. Initialization uses patterns of motion encoded as a set of soft constraints that are expected to hold approximately during an initialization period. Penalty metrics are defined to measure the deviation of calculated motion trajectories from the soft constraints. Differential equations of motion for an inertial sensor are solved with the initial conditions as variables; the initial conditions that minimize the penalty metrics are used as estimates for the actual initial conditions of the sensor. Soft constraints and penalty metrics for a specific application are chosen based on the types of motion patterns expected for this application. Illustrative cases include applications with relatively little movement during initialization, and applications with approximately periodic motion during initialization.

    摘要翻译： 用于惯性传感器的初始化方法，其估计起始方向和速度，而不需要传感器在静止或公知的位置或取向开始。 初始化使用被编码为一组软约束的运动模式，预期在初始化期间将保持约束。 惩罚度量被定义为测量计算的运动轨迹与软约束的偏差。 惯性传感器的运动微分方程用初始条件作为变量求解; 使用最小化惩罚度量的初始条件用作传感器的实际初始条件的估计。 基于针对该应用预期的运动模式的类型来选择特定应用的软约束和惩罚度量。 说明性的情况包括初始化期间移动相对较少的应用程序，以及在初始化期间具有大致周期性运动的应用程序。