OCCUPANT EVALUATION USING MULTI-MODAL SENSOR FUSION FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS

    公开(公告)号:US20250022289A1

    公开(公告)日:2025-01-16

    申请号:US18349827

    申请日:2023-07-10

    Abstract: In various examples, occupant assessment using multi-modal sensor fusion for monitoring systems and applications are provided. In some embodiments, an occupant monitoring system comprises an occupant evaluation function that may predict at least one characteristic representative of a size of the occupant. The occupant evaluation function may include a first processing path that generates a representation of features corresponding to the occupant based on optical image data, and a second processing path that performs operations to determine a depth corresponding to the one or more features based on depth data derived from the optical image data and the point cloud depth data. In some embodiments, a three-dimensional pose detection model generates a three-dimensional pose estimate of the occupant using the optical image data, and the three-dimensional pose estimate is scaled to an absolute pose based on the point cloud depth data.

    USER AUTHENTICATION FOR VEHICLE ACCESS AND IN-CABIN EXPERIENCE USING INFRARED IMAGING

    公开(公告)号:US20250065844A1

    公开(公告)日:2025-02-27

    申请号:US18453963

    申请日:2023-08-22

    Abstract: In various examples, infrared image data may be used to detect a subcutaneous characteristic(s) (e.g., a palm vein topology) of a person (e.g., a person requesting entry to a vehicle, a vehicle occupant) and authenticate the user based on the detected subcutaneous characteristic(s). For example, infrared image data representing one or more acquired subcutaneous characteristics (e.g., a topology of veins and/or other blood vessels in a region of the authenticating user's palm, hand, neck, forearm, face, fingertip, eye, etc.) may be generated. Hand and/or palm detection may be applied to detect a region depicting the user's hand or palm, and that region (or some subset thereof) may be segmented to generate a representation of an acquired vein topology. The acquired vein topology may be compared with one or more reference vein topologies stored in a database to determine whether the acquired vein topology matches one of the reference vein topologies.

    CHILD PRESENCE DETECTION FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS

    公开(公告)号:US20250022288A1

    公开(公告)日:2025-01-16

    申请号:US18219969

    申请日:2023-07-10

    Abstract: In various examples, sensor data (e.g., image and/or RADAR data) may be used to detect occupants and classify them (e.g., as children or adults) using one or more predictions that represent estimated age (e.g., based on detected limb length, a detected face) and/or detected child presence (e.g., based on detecting an occupied child seat). In some embodiments, multiple predictions generated using multiple machine learning models (and optionally one or more corresponding confidence values) may be combined using a state machine and/or one or more machine learning models to generate a combined assessment of occupant presence and/or age for each occupant and/or supported occupant slot. As such, the techniques described herein may be utilized to detect child presence, detect unattended child presence, determine age or size of a particular occupant, and/or take some responsive action (e.g., trigger an alarm, control temperature, unlock door(s), permit or disable airbag deployment, etc.).

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