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    Autonomous Vehicle Utilizing Pose Estimation
    22.
    发明申请
    Autonomous Vehicle Utilizing Pose Estimation 审中-公开

    公开(公告)号：US20190063932A1

    公开(公告)日：2019-02-28

    申请号：US16100462

    申请日：2018-08-10

    Applicant: NEC Laboratories America, Inc.

    Inventor： Quoc-Huy Tran ,  Manmohan Chandraker ,  Hyo Jin Kim

    IPC: G01C21/32 ,  G05D1/00 ,  G06T7/73 ,  G06N3/08 ,  G06N5/04 ,  G06F17/30

    Abstract: A computer-implemented method, system, and computer program product are provided for a guidance control system utilizing pose estimation in an autonomous vehicle. The method includes receiving, by a pose estimation system, a plurality of images from one or more cameras. The method also includes predicting, by the pose estimation system, a pose from the score map and a combined feature map, the combined feature map correlated from a pair of the plurality of images. The method additionally includes moving, by a propulsion system, the autonomous vehicle responsive to the pose.

    Joint rolling shutter image stitching and rectification
    25.
    发明授权
    Joint rolling shutter image stitching and rectification 有权

    公开(公告)号：US11694311B2

    公开(公告)日：2023-07-04

    申请号：US17182836

    申请日：2021-02-23

    Applicant: NEC Laboratories America, Inc.

    Inventor： Bingbing Zhuang ,  Quoc-Huy Tran

    IPC: G06T5/00 ,  G06T7/20 ,  H04N23/68

    CPC classification number: G06T5/003 ,  G06T7/20 ,  H04N23/689

    Abstract: A computer-implemented method executed by at least one processor for applying rolling shutter (RS)-aware spatially varying differential homography fields for simultaneous RS distortion removal and image stitching is presented. The method includes inputting two consecutive frames including RS distortions from a video stream, performing keypoint detection and matching to extract correspondences between the two consecutive frames, feeding the correspondences between the two consecutive frames into an RS-aware differential homography estimation component to filter out outlier correspondences, sending inlier correspondences to an RS-aware spatially varying differential homography field estimation component to compute an RS-aware spatially varying differential homography field, and using the RS-aware spatially varying differential homography field in an RS stitching and correction component to produce stitched images with removal of the RS distortions.

    DENSE THREE-DIMENSIONAL CORRESPONDENCE ESTIMATION WITH MULTI-LEVEL METRIC LEARNING AND HIERARCHICAL MATCHING
    27.
    发明申请
    DENSE THREE-DIMENSIONAL CORRESPONDENCE ESTIMATION WITH MULTI-LEVEL METRIC LEARNING AND HIERARCHICAL MATCHING 审中-公开

    公开(公告)号：US20200058156A1

    公开(公告)日：2020-02-20

    申请号：US16526306

    申请日：2019-07-30

    Applicant: NEC Laboratories America, Inc.

    Inventor： Quoc-Huy Tran ,  Mohammed E. Fathy Salem ,  Muhammad Zeeshan Zia ,  Paul Vernaza ,  Manmohan Chandraker

    IPC: G06T15/08 ,  G06K9/62 ,  G06K9/72 ,  G06N3/04 ,  G06N3/08 ,  G06T15/10

    Abstract: A method for estimating dense 3D geometric correspondences between two input point clouds by employing a 3D convolutional neural network (CNN) architecture is presented. The method includes, during a training phase, transforming the two input point clouds into truncated distance function voxel grid representations, feeding the truncated distance function voxel grid representations into individual feature extraction layers with tied weights, extracting low-level features from a first feature extraction layer, extracting high-level features from a second feature extraction layer, normalizing the extracted low-level features and high-level features, and applying deep supervision of multiple contrastive losses and multiple hard negative mining modules at the first and second feature extraction layers. The method further includes, during a testing phase, employing the high-level features capturing high-level semantic information to obtain coarse matching locations, and refining the coarse matching locations with the low-level features to capture low-level geometric information for estimating precise matching locations.

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