APPARATUS AND METHODS FOR OBJECT DETECTION USING MACHINE LEARNING PROCESSES

    公开(公告)号:US20240331372A1

    公开(公告)日:2024-10-03

    申请号:US18738636

    申请日:2024-06-10

    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.

    PROXIMITY-BASED PROTOCOL FOR ENABLING MULTI-USER EXTENDED REALITY (XR) EXPERIENCE

    公开(公告)号:US20240242443A1

    公开(公告)日:2024-07-18

    申请号:US18153498

    申请日:2023-01-12

    Abstract: Systems and techniques are described herein for enabling a multi-user extended reality (XR) experience. In one illustrative example, a user device can receive, associated with a user from a host device, a message comprising a prompt to join an XR room hosted by the host device. The user device can connect to the host device based on the message. The user device can can obtain images of a three-dimensional (3D) scene of a physical environment and can transmit the images to the host device. The user device can receive synthetic content from the host device. A virtual representation of the user can be localized with respect to the XR room based on features in the images matched with features of the 3D scene of the physical environment. The user device can render the synthetic content for the XR room based on a pose of the apparatus.

    THREE-DIMENSIONAL SCAN REGISTRATION WITH DEFORMABLE MODELS

    公开(公告)号:US20220215564A1

    公开(公告)日:2022-07-07

    申请号:US17144102

    申请日:2021-01-07

    Abstract: Systems and techniques are provided for registering three-dimensional (3D) images to deformable models. An example method can include determining, based on an image of a target and associated depth information, a 3D mesh of the target; determining different sets of rotation and translation parameters based on modifications to rotation and translation parameters of the 3D mesh; generating, based on the different sets of rotation and translation parameters, different 3D meshes having different orientations, different poses, and/or different alignments relative to the target; determining different sets of model parameters associated with the different 3D meshes, based on modifications to the different sets of rotation and translation parameters; generating, based on the different sets of model parameters, different additional 3D meshes having different orientations, different poses, and/or different alignments relative to the target; and selecting a final 3D mesh of the target from the different additional 3D meshes.

    SYSTEMS AND METHODS FOR NON-OBSTACLE AREA DETECTION

    公开(公告)号:US20190333229A1

    公开(公告)日:2019-10-31

    申请号:US16509043

    申请日:2019-07-11

    Abstract: A method performed by an electronic device is described. The method includes generating a depth map of a scene external to a vehicle. The method also includes performing first processing in a first direction of a depth map to determine a first non-obstacle estimation of the scene. The method also includes performing second processing in a second direction of the depth map to determine a second non-obstacle estimation of the scene. The method further includes combining the first non-obstacle estimation and the second non-obstacle estimation to determine a non-obstacle map of the scene. The combining includes combining comprises selectively using a first reliability map of the first processing and/or a second reliability map of the second processing The method additionally includes navigating the vehicle using the non-obstacle map.

    CACHE MEMORY ARCHITECTURE AUGMENTATION FOR 3-DIMENSIONAL (3D) DATA

    公开(公告)号:US20250117876A1

    公开(公告)日:2025-04-10

    申请号:US18481909

    申请日:2023-10-05

    Abstract: Aspects of the disclosure are directed to reordering a plurality of input block voxel indices in a cache memory. In accordance with one aspect, an apparatus including a create block configured to receive the plurality of input block voxel indices and configured to generate a reordered list based on the plurality of input block voxel indices; and an integrate block coupled to the create block, the integrate block configured to use the reordered list to deliver integrate depth data for generating a plurality of output block voxel indices. In accordance with one aspect, a method including reordering the plurality of input block voxel indices into a plurality of output block voxel indices using a separated set of input block voxel indices; and accessing the plurality of output block voxel indices to provide an augmented cache memory access.

    MULTI-FRAME THREE-DIMENSIONAL (3D) RECONSTRUCTION

    公开(公告)号:US20250086889A1

    公开(公告)日:2025-03-13

    申请号:US18465904

    申请日:2023-09-12

    Abstract: Disclosed are systems and techniques for image processing. For example, a computing device can project a sample location (of a plurality of sample locations) of a block of a scene onto depth frames to determine pixel values for the sample location. Each of the depth frames corresponds to a pose and includes a depth prediction value corresponding to the sample location. The computing device can read the depth prediction values of the depth frames at the pixel values for the sample location on each depth frame of the depth frames. The computing device can obtain 3D points of the depth prediction values in a three-dimensional (3D) space. The computing device can then generate weighted depth prediction values by assigning a weight to each depth prediction value of the depth prediction values. The computing device can update the sample location based on the weighted depth prediction values.

    ENHANCING THREE-DIMENSIONAL MODELS USING MULTI-VIEW REFINEMENT

    公开(公告)号:US20220230406A1

    公开(公告)日:2022-07-21

    申请号:US17153773

    申请日:2021-01-20

    Abstract: Systems and techniques are provided for modeling three-dimensional (3D) meshes using multi-view image data. An example method can include determining, based on a first image of a target, first 3D mesh parameters for the target corresponding to a first coordinate frame; determining, based on a second image of the target, second 3D mesh parameters for the target corresponding to a second coordinate frame; determining third 3D mesh parameters for the target in a third coordinate frame, the third 3D mesh parameters being based on the first and second 3D mesh parameters and relative rotation and translation parameters of image sensors that captured the first and second images; determining a loss associated with the third 3D mesh parameters, the loss being based on the first and second 3D mesh parameters and the relative rotation and translation parameters; determining 3D mesh parameters based on the loss and third 3D mesh parameters.

    CONTENT-ADAPTIVE 3D RECONSTRUCTION

    公开(公告)号:US20250086877A1

    公开(公告)日:2025-03-13

    申请号:US18465930

    申请日:2023-09-12

    Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for content adaptive 3D reconstruction. A graphics processor may compute a curvature of content in a block volume that represents a 3D scene, where the block volume includes a set of voxels. The graphics processor may select a number of the set of voxels in the block volume based on the computed curvature of the content. The graphics processor may output an indication of the selected number of the set of voxels in the block volume.

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