APPARATUS AND METHODS FOR OBJECT DETECTION USING MACHINE LEARNING PROCESSES

    公开(公告)号:US20230206613A1

    公开(公告)日:2023-06-29

    申请号:US17561299

    申请日:2021-12-23

    CPC classification number: G06V10/82 G06V10/25 G06V10/72 G06V10/764 G06V40/107

    Abstract: Methods, systems, and apparatuses are provided to automatically detect objects within images. For example, an image capture device may capture an image, and may apply a trained neural network to the image to generate an object value and a class value for each of a plurality of portions of the image. Further, the image capture device may determine, for each of the plurality of image portions, a confidence value based on the object value and the class value corresponding to each image portion. The image capture device may also detect an object within at least one image portion based on the confidence values. Further, the image capture device may output a bounding box corresponding to the at least one image portion. The bounding box defines an area of the image that includes one or more objects.

    MODELING OBJECTS FROM MONOCULAR CAMERA OUTPUTS

    公开(公告)号:US20220277489A1

    公开(公告)日:2022-09-01

    申请号:US17189105

    申请日:2021-03-01

    Abstract: Systems and techniques are provided for modeling three-dimensional (3D) meshes using images. An example method can include receiving, via a neural network system, an image of a target and metadata associated with the image and/or a device that captured the image; determining, based on the image and metadata, first 3D mesh parameters of a first 3D mesh of the target, the first 3D mesh parameters and first 3D mesh corresponding to a first reference frame associated with the image and/or the device; and determining, based on the first 3D mesh parameters, second 3D mesh parameters for a second 3D mesh of the target, the second 3D mesh parameters and second 3D mesh corresponding to a second reference frame, the second reference frame including a 3D coordinate system of a real-world scene where the target is located.

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