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    PEDESTRIAN DEAD RECKONING USING DIFFERENTIAL GEOMETRIC PROPERTIES OF HUMAN GAIT
    71.
    发明公开
    PEDESTRIAN DEAD RECKONING USING DIFFERENTIAL GEOMETRIC PROPERTIES OF HUMAN GAIT 审中-公开

    公开(公告)号：US20240094000A1

    公开(公告)日：2024-03-21

    申请号：US18240230

    申请日：2023-08-30

    Applicant: Apple Inc.

    Inventor： Ryan K. Burns ,  Xiaoyuan Tu

    IPC: G01C21/12 ,  G01C21/20

    CPC classification number: G01C21/12 ,  G01C21/206

    Abstract: In some embodiments, a method comprises: receiving acceleration data from a motion sensor of a mobile device carried by a user, the acceleration data represented by a space curve in a three-dimensional (3D) acceleration space, the space curve indicative of a cyclical vertical displacement of the user's center of mass accompanied by a lateral left and right sway of the center of mass when the user is stepping; computing a tangent-normal-binormal (TNB) reference frame from the acceleration data, the TNB reference frame describing instantaneous geometric and kinematic properties of the space curve over time; and computing a direction of travel of the user based on an orientation of a unit binormal (B) vector of the TNB reference frame in the 3D acceleration space, and computing a speed of the user based on a linear regression model applied to the kinematic properties of the TNB reference frame.

    User posture change detection for head pose tracking in spatial audio applications
    74.
    发明授权
    User posture change detection for head pose tracking in spatial audio applications 有权

    公开(公告)号：US11675423B2

    公开(公告)日：2023-06-13

    申请号：US17351195

    申请日：2021-06-17

    Applicant: Apple Inc.

    Inventor： Mehmet Akgul ,  Alexander Singh Alvarado ,  Xiaoyuan Tu ,  Margaret H. Tam

    IPC: G06F3/01 ,  H04S7/00 ,  G01P15/18

    CPC classification number: G06F3/012 ,  H04S7/304 ,  G01P15/18

    Abstract: Embodiments are disclosed for user posture change detection for triggering re-centering of spatial audio. In an embodiment, a method comprises: obtaining source device motion data from a source device and headset motion data from a headset worn by a user; estimating a gravity vector from one of the source device or headset motion data; splitting the source device and headset motion data into vertical and horizontal planes, the vertical plane in the direction of the estimated gravity vector and the horizontal plane perpendicular to the estimated gravity vector; calculating similarity measures based on the source device motion data and headset motion data in the vertical and horizontal planes over a time window; detecting a posture change event based on the calculated similarity measures; and resetting a head tracker error after the detected user posture change event.

    Raise gesture detection in a device
    76.
    发明授权
    Raise gesture detection in a device 有权

    公开(公告)号：US10303239B2

    公开(公告)日：2019-05-28

    申请号：US16130725

    申请日：2018-09-13

    Applicant: Apple Inc.

    Inventor： Xiaoyuan Tu ,  Anil K. Kandangath ,  Adam S. Howell

    IPC: G06F1/32 ,  G06F1/3234 ,  G06F3/01 ,  G06F1/16 ,  G06F1/3287 ,  G06F1/3206 ,  G06F1/3296 ,  G06F1/3218

    Abstract: A wearable computing device can detect device-raising gestures. For example, onboard motion sensors of the device can detect movement of the device in real time and infer information about the spatial orientation of the device. Based on analysis of signals from the motion sensors, the device can detect a raise gesture, which can be a motion pattern consistent with the user moving the device's display into his line of sight. In response to detecting a raise gesture, the device can activate its display and/or other components. Detection of a raise gesture can occur in stages, and activation of different components can occur at different stages.

    Motion pattern classification and gesture recognition
    78.
    发明授权
    Motion pattern classification and gesture recognition 有权

    公开(公告)号：US10209778B2

    公开(公告)日：2019-02-19

    申请号：US14828422

    申请日：2015-08-17

    Applicant: Apple Inc.

    Inventor： Christopher Moore ,  Xiaoyuan Tu ,  William Matthew Vieta

    IPC: G09G5/00 ,  G06F3/01 ,  G06F3/0488 ,  G06F3/0484 ,  G06K9/00

    Abstract: Methods, program products, and systems for gesture classification and recognition are disclosed. In general, in one aspect, a system can determine multiple motion patterns for a same user action (e.g., picking up a mobile device from a table) from empirical training data. The system can collect the training data from one or more mobile devices. The training data can include multiple series of motion sensor readings for a specified gesture. Each series of motion sensor readings can correspond to a particular way a user performs the gesture. Using clustering techniques, the system can extract one or more motion patterns from the training data. The system can send the motion patterns to mobile devices as prototypes for gesture recognition.

    Mobile device sensor data subscribing and sharing
    80.
    发明授权
    Mobile device sensor data subscribing and sharing 有权

    公开(公告)号：US09794729B2

    公开(公告)日：2017-10-17

    申请号：US15045021

    申请日：2016-02-16

    Applicant: Apple Inc.

    Inventor： Libo C. Meyers ,  Anil K. Kandangath ,  Xiaoyuan Tu

    IPC: H04L29/00 ,  H04W4/00 ,  H04L29/06 ,  H04W12/08 ,  H04W64/00 ,  H04W76/02

    CPC classification number: H04W4/70 ,  H04L63/10 ,  H04W4/80 ,  H04W12/08 ,  H04W64/00 ,  H04W76/10

    Abstract: Techniques for mobile devices to subscribe and share raw sensor data are provided. The raw sensor data associated with sensors (e.g., accelerometers, gyroscopes, compasses, pedometers, pressure sensors, audio sensors, light sensors, barometers) of a mobile device can be used to determine the movement or activity of a user. By sharing the raw or compressed sensor data with other computing devices, the other computing devices can determine a motion state based on the sensor data. Additionally, in some instances, the other computing devices can determine a functional state based on the sensor data and the motion state. For example, functional state classification can be associated with each motion state (e.g., driving, walking) by further describing each motion state (e.g., walking on rough terrain, driving while texting).

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