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    CAMERA-ONLY-LOCALIZATION IN SPARSE 3D MAPPED ENVIRONMENTS
    2.
    发明申请
    CAMERA-ONLY-LOCALIZATION IN SPARSE 3D MAPPED ENVIRONMENTS 有权

    公开(公告)号：US20220392108A1

    公开(公告)日：2022-12-08

    申请号：US17887580

    申请日：2022-08-15

    Applicant: TEXAS INSTRUMENTS INCORPORATED

    Inventor： Hrushikesh Tukaram GARUD ,  Deepak PODDAR ,  Soyeb Noormohammed NAGORI

    IPC: G06T7/73 ,  G01C21/30 ,  B60R1/00 ,  G06V10/46

    Abstract: Techniques for localizing a vehicle include obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.

    OPTICAL FLOW DETERMINATION USING PYRAMIDAL BLOCK MATCHING
    3.
    发明申请
    OPTICAL FLOW DETERMINATION USING PYRAMIDAL BLOCK MATCHING 有权
    使用PYRAMIDAL块匹配的光流测定

    公开(公告)号：US20150365696A1

    公开(公告)日：2015-12-17

    申请号：US14737904

    申请日：2015-06-12

    Applicant: TEXAS INSTRUMENTS INCORPORATED

    Inventor： Hrushikesh Tukaram GARUD ,  Soyeb Noormohammed NAGORI ,  Dipan Kumar MANDAL

    IPC: H04N19/53 ,  H04N19/523 ,  H04N19/56 ,  H04N19/20 ,  H04N19/513

    CPC classification number: H04N19/53 ,  H04N19/56

    Abstract: An image processing system includes a processor and optical flow determination logic. The optical flow determination logic is to quantify relative motion of a feature present in a first frame of video and a second frame of video with respect to the two frames of video. The optical flow determination logic configures the processor to convert each of the frames of video into a hierarchical image pyramid. The image pyramid comprises a plurality of image levels. Image resolution is reduced at each higher one of the image levels. For each image level and for each pixel in the first frame, the processor is configured to establish an initial estimate of a location of the pixel in the second frame and to apply a plurality of sequential searches, starting from the initial estimate, that establish refined estimates of the location of the pixel in the second frame.

    Abstract translation: 图像处理系统包括处理器和光流确定逻辑。 光流确定逻辑是量化相对于两帧视频的视频第一帧和第二帧视频中存在的特征的相对运动。 光流确定逻辑配置处理器以将每个视频帧转换为分层图像金字塔。 图像金字塔包括多个图像级别。 图像分辨率在每个较高的一个图像级别被减少。 对于每个图像级别和对于第一帧中的每个像素，处理器被配置为建立第二帧中的像素的位置的初始估计，并且从初始估计开始施加多个顺序搜索，其建立精确的 估计第二帧中像素的位置。

    CAMERA-ONLY-LOCALIZATION IN SPARSE 3D MAPPED ENVIRONMENTS
    5.
    发明申请
    CAMERA-ONLY-LOCALIZATION IN SPARSE 3D MAPPED ENVIRONMENTS 审中-公开

    公开(公告)号：US20200334857A1

    公开(公告)日：2020-10-22

    申请号：US16854590

    申请日：2020-04-21

    Applicant: TEXAS INSTRUMENTS INCORPORATED

    Inventor： Hrushikesh Tukaram GARUD ,  Deepak PODDAR ,  Soyeb Noormohammed NAGORI

    IPC: G06T7/73 ,  G01C21/30 ,  B60R1/00 ,  G06K9/46

    Abstract: Techniques for localizing a vehicle are provided that include obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.

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