3D Object Detection Using Random Forests

    公开(公告)号:US20220292717A1

    公开(公告)日:2022-09-15

    申请号:US17636250

    申请日:2019-09-13

    Applicant: Google LLC

    Abstract: Example embodiments allow for fast, efficient detection and pose estimation of objects based on point clouds, depth images/maps, or other depth information about a scene that may contain the objects. Embodiments include translating and rotating the depth image to bring individual points of the depth image to a standard orientation and location so as to improve performance when an object is near the periphery of the field of view. Some disclosed embodiments include applying a random forest to perform pose estimation. By using the decision trees or other fast methods, it can be advantageous to perform pose estimation a plurality of times prior to identifying whether a particular object is actually present in a scene. Prospective pose estimates can be combined with models of the objects in order to evaluate whether the object is present in the scene.

    3D object detection using random forests

    公开(公告)号:US12236639B2

    公开(公告)日:2025-02-25

    申请号:US17636250

    申请日:2019-09-13

    Applicant: Google LLC

    Abstract: Example embodiments allow for fast, efficient detection and pose estimation of objects based on point clouds, depth images/maps, or other depth information about a scene that may contain the objects. Embodiments include translating and rotating the depth image to bring individual points of the depth image to a standard orientation and location so as to improve performance when an object is near the periphery of the field of view. Some disclosed embodiments include applying a random forest to perform pose estimation. By using the decision trees or other fast methods, it can be advantageous to perform pose estimation a plurality of times prior to identifying whether a particular object is actually present in a scene. Prospective pose estimates can be combined with models of the objects in order to evaluate whether the object is present in the scene.

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