Device and method for color indentification

    公开(公告)号:US12104958B2

    公开(公告)日:2024-10-01

    申请号:US17777091

    申请日:2020-11-16

    CPC classification number: G01J3/462 G01J3/513 G01J2003/1213

    Abstract: Devices and methods of the present technology utilize wavelength-dependent transmittance of 2D materials to identify the wavelength of an electromagnetic radiation. A wide range of 2D materials can be used, making possible the use of the technology over a large portion of the electromagnetic spectrum, from gamma rays to the far infrared. When combined with appropriate algorithms and artificial intelligence, the technology can identify the wavelength of one or more monochromatic sources, or can identify color through the use of a training set. When applied in an array format, the technology can provide color imaging or spectral imaging using different regions of the electromagnetic spectrum.

    Method and system for in-bed contact pressure estimation via contactless imaging

    公开(公告)号:US12226203B2

    公开(公告)日:2025-02-18

    申请号:US17831993

    申请日:2022-06-03

    Abstract: Provided herein are systems and methods for estimating contact pressure of a human lying on a surface including one or more imaging devices having imaging sensors oriented toward the surface, a processor and memory, including a trained model for estimating human contact pressure trained with a dataset including a plurality of human lying poses including images generated from at least one of a plurality of imaging modalities including at least one of a red-green-blue modality, a long wavelength infrared modality, a depth modality, or a pressure map modality, wherein the processor can receive one or more images from the imaging devices of the human lying on the surface and a source of one or more physical parameters of the human to determine a pressure map of the human based on the one or more images and the one or more physical parameters.

    3D human pose estimation system
    4.
    发明授权

    公开(公告)号:US12288360B2

    公开(公告)日:2025-04-29

    申请号:US17403933

    申请日:2021-08-17

    Abstract: Methods and systems for providing a dataset of human in-bed poses include simultaneously gathered images of in-bed poses of humans from imaging modalities including red-green-blue (RGB) and one or more of long wavelength infrared (LWIR), depth imaging, and pressure mapping. The images are obtained under a lighting condition and a cover condition. The dataset can be used to train a model of estimating human in-bed poses and for methods of estimating human in-bed poses. Methods and systems of estimating three-dimensional human poses from two-dimensional input images are provided.

    Methods and systems for in-bed pose estimation

    公开(公告)号:US11222437B2

    公开(公告)日:2022-01-11

    申请号:US16778459

    申请日:2020-01-31

    Abstract: Non-contact methods and systems are disclosed for estimating an in-bed human pose. The method includes the steps of: (a) capturing thermal imaging data of a human subject lying on a bed using a long wavelength infrared camera positioned above the human subject; (b) transmitting the thermal imaging data to a computer system; and (c) processing the thermal imaging data by the computer system using a model to estimate the pose of the human subject, the model comprising a machine learning inference model trained on a training dataset of a plurality of in-bed human poses.

    METHODS AND SYSTEMS FOR IN-BED POSE ESTIMATION

    公开(公告)号:US20200265602A1

    公开(公告)日:2020-08-20

    申请号:US16778459

    申请日:2020-01-31

    Abstract: Non-contact methods and systems are disclosed for estimating an in-bed human pose. The method includes the steps of: (a) capturing thermal imaging data of a human subject lying on a bed using a long wavelength infrared camera positioned above the human subject; (b) transmitting the thermal imaging data to a computer system; and (c) processing the thermal imaging data by the computer system using a model to estimate the pose of the human subject, the model comprising a machine learning inference model trained on a training dataset of a plurality of in-bed human poses.

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