TARGET AREA DETECTION DEVICE, TARGET AREA DETECTION METHOD, AND TARGET AREA DETECTION PROGRAM

    公开(公告)号:US20230093034A1

    公开(公告)日:2023-03-23

    申请号:US17802081

    申请日:2020-02-26

    Abstract: A candidate detection unit 118 detects, for each of a plurality of target images, candidate regions representing a specific detection target region using a discriminator. A region-label acquisition unit 120 acquires, for a part of the target images, position information of a search region as a teacher label. A region specifying unit 121 imparts, based on the part of the target images and the acquired position information of the search region, the position information of the search region to each of the target images, which are not the part of the target images, in semi-supervised learning processing. A filtering unit 122 outputs, for each of the acquired plurality of target images, among the candidate regions, a candidate region, an overlapping degree of which with the search region is equal to or larger than a fixed threshold.

    OBJECT DETECTION DEVICE, METHOD, AND PROGRAM

    公开(公告)号:US20210209403A1

    公开(公告)日:2021-07-08

    申请号:US17251172

    申请日:2019-05-07

    Abstract: Even if an object to be detected is not remarkable in images, and the input includes images including regions that are not the object to be detected and have a common appearance on the images, a region indicating the object to be detected is accurately detected. A local feature extraction unit 20 extracts a local feature of a feature point from each image included in an input image set. An image-pair common pattern extraction unit 30 extracts, from each image pair selected from images included in the image set, a common pattern constituted by a set of feature point pairs that have similar local features extracted by the local feature extraction unit 20 in images constituting the image pair, the set of feature point pairs being geometrically similar to each other. A region detection unit 50 detects, as a region indicating an object to be detected in each image included in the image set, a region that is based on a common pattern that is omnipresent in the image set, of common patterns extracted by the image-pair common pattern extraction unit 30.

    GEOMETRIC TRANSFORMATION MATRIX ESTIMATING DEVICE, GEOMETRIC TRANSFORMATION MATRIX ESTIMATING METHOD, AND PROGRAM

    公开(公告)号:US20210201440A1

    公开(公告)日:2021-07-01

    申请号:US17058089

    申请日:2019-05-28

    Abstract: An object is to make it possible to precisely infer a geometric transformation matrix for transformation between an image and a reference image representing a plane region even if correspondence to the reference image cannot be obtained. A first line segment group extraction unit 120 extracts, out of a line segment group in an image, line segments that correspond to a direction that is parallel or perpendicular to a side of a rectangle included in the image, from the inside of the rectangle, takes the extracted line segments to be a first line segment group, and extracts a plurality of line segments different from the first line segment group out of the line segment group. An endpoint detection unit 150 detects four intersection points between ends of the image and two line segments that are selected from line segments that correspond to a direction that is parallel or perpendicular to a side of the rectangle and are extracted from a plurality of line segments obtained by transforming the different line segments using an affine transformation matrix in which an angle of the first line segment group relative to a reference direction of the image is used as a rotation angle. A homography matrix inferring unit 160 computes a geometric transformation matrix based on the affine transformation matrix and a homography matrix computed based on correspondence between the four intersection points and the four vertexes of the rectangle in a reference image.

    IMAGE CORRECTION DEVICE, IMAGE CORRECTION METHOD, AND IMAGE CORRECTION PROGRAM

    公开(公告)号:US20250045875A1

    公开(公告)日:2025-02-06

    申请号:US18716828

    申请日:2021-12-07

    Abstract: An input processing unit receives an image and a three-dimensional point cloud including three-dimensional points having reflection intensity on a surface of an object for which at least a relationship between an image capturing position and a measurement position is obtained in advance, and obtains pixel positions on the image corresponding to the respective three-dimensional points of the three-dimensional point cloud. A shadow region estimation unit performs clustering on pixels of the image on the basis of pixel values and pixel positions, obtains an average reflection intensity and an average value of quantified color information for each of clusters, and estimates a shadow region by performing comparison in the average reflection intensity and the average value of the color information between the clusters. A shadow correction unit corrects pixel values of the shadow region from the shadow region estimated and the image.

    POINT CLOUD COMPLETION DEVICE, POINT CLOUD COMPLETION METHOD, AND POINT CLOUD COMPLETION PROGRAM

    公开(公告)号:US20240371093A1

    公开(公告)日:2024-11-07

    申请号:US18689055

    申请日:2021-09-06

    Abstract: A point cloud complementing device 100 receives a colored three-dimensional point cloud of each point including a missing region and the number of points to be complemented as inputs. A CPU 11 of the point cloud complementing device 100 extracts a feature vector of the three-dimensional point cloud using a feature extractor learned in advance. The CPU 11 uses a point cloud complementing model learned in advance in consideration of an error between color information and brightness information, has the feature vector and the number of points to be complemented as inputs, and outputs a point cloud obtained by complementing the input three-dimensional point cloud up to the number of points to be complemented by performing correction on point at which the brightness does not change among adjacent points of a predicted point cloud such that the points have close brightness information assuming that the points are on the same plane.

    POSITION DETECTION DEVICE, POSITION DETECTION METHOD, AND POSITION DETECTION PROGRAM

    公开(公告)号:US20240312047A1

    公开(公告)日:2024-09-19

    申请号:US18577966

    申请日:2021-07-14

    Abstract: There is provided a position detection device that recognizes a presence position of a target object in a three-dimensional space. The device acquires three-dimensional point cloud information of the space and a plurality of images obtained by imaging an area including surroundings of an object in the space from different imaging points. A region detection unit receives, as an input, the plurality of acquired images, determines whether a target object appears in the plurality of images, and detects a region of the object in each of the plurality of images in a case where the target object appears in each of the images. A specifying unit specifies a region of a point cloud corresponding to the target object based on the point cloud information and the region of the object detected in each of the images. A position detection unit specifies a position of the target object in the space by recognizing points corresponding to the target object from the point cloud information of the region specified by the specifying unit.

    3D POINT CLOUD IDENTIFICATION DEVICE, 3D POINT CLOUD IDENTIFICATION METHOD, AND 3D POINT CLOUD IDENTIFICATION PROGRAM

    公开(公告)号:US20240281501A1

    公开(公告)日:2024-08-22

    申请号:US18292226

    申请日:2021-07-29

    CPC classification number: G06F18/241

    Abstract: A three-dimensional point group is accurately identified on the basis of GIS data in which a geographical position of an object is defined by a polygon, a line, or a point.
    An initial label assignment unit (101) assigns a label indicating an object or a type of the object corresponding to some three-dimensional points included in a three-dimensional point group to the three-dimensional points on the basis of GIS data indicating a geographical position of the object by a polygon formed by connecting a plurality of coordinate points, a line formed by connecting a plurality of coordinate points, or one coordinate point itself, and an estimation unit (112) estimates a label of three-dimensional points to which the label has not been assigned by propagating the label of the three-dimensional points to which the label has been assigned to the three-dimensional points to which the label has not been assigned based on similarity between the three-dimensional points to which the label has been assigned and the three-dimensional points to which the label has not been assigned.

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