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1.发明申请公开(公告)号：US20220254173A1
公开(公告)日：2022-08-11
申请号：US17627883
申请日：2019-07-23
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Yasuhiro YAO , Hitoshi NIIGAKI , Kana KURATA , Shingo ANDO , Atsushi SAGATA
IPC: G06V20/64 , G06T7/60 , G06V10/46 , G06V10/762 , G06V10/764
Abstract: A mesh structure facility detection device that detects data corresponding to a mesh structure facility from three-dimensional structure data representing a space including an outer shape of an object, includes: a projection unit that projects the three-dimensional structure data in a predetermined direction to obtain two-dimensional structure data; and a detection unit that detects a point included in a region in which the two-dimensional structure data has a density of more than or equal to a predetermined threshold value as a point corresponding to the mesh structure facility.
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公开(公告)号：US20220230347A1
公开(公告)日：2022-07-21
申请号：US17608975
申请日：2019-05-08
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Hitoshi NIIGAKI , Masaki WAKI , Masaaki INOUE , Yasuhiro YAO , Tomoya SHIMIZU , Hiroyuki OSHIDA , Kana KURATA , Shingo ANDO , Atsushi SAGATA
Abstract: It is possible to estimate a slack level accurately in consideration of a shape of a deformed cable. A point cloud analysis device sets a plurality of regions of interest obtained by window-searching a wire model including a quadratic curve model representing a cable obtained from a point cloud consisting of three-dimensional points on an object, the region of interest being divided into a first region and a second region. The point cloud analysis device compares information on the first region with information on the second region based on the point cloud included in the region of interest and the quadratic curve model for each of the plurality of regions of interest, calculates a degree of division boundary representing a degree to which a division position between the first region and the second region of the plurality of regions of interest is a branch point of the cable, and detects a division boundary point that is a branch point of a cable represented by the quadratic curve model based on the degree of division boundary calculated for each of the plurality of regions of interest.
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公开(公告)号：US20220327779A1
公开(公告)日：2022-10-13
申请号：US17634595
申请日：2019-08-19
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Masaaki INOUE , Hitoshi NIIGAKI , Yukihiro GOTO , Shigehiro MATSUDA , Toshiya OHIRA , Ryuji HONDA , Tomoya SHIMIZU , Hiroyuki OSHIDA
Abstract: An object of the present disclosure is to provide a technique for creating a three-dimensional model of a line-like structure from a point cloud obtained using three-dimensional laser measuring equipment and detecting a three-dimensional model of a cable. A detection apparatus according to the disclosure includes a point cloud data input unit 12 that reads point cloud data where a structure that is present in a three-dimensional space is represented by a point cloud that is present in the three-dimensional space, a rule-based three-dimensional model generation unit 15 that combines linearly disposed point clouds into a group and generates a three-dimensional model of a line-like structure using a direction vector configured with point clouds included in the group, a machine learning-based three-dimensional model generation unit 14 that generates a three-dimensional model of a line-like structure based on a database that links point clouds and line-like structures, and a three-dimensional model merging unit that selects one of a plurality of three-dimensional models of line-like structures generated at an identical position in the three-dimensional space as a three-dimensional model of a line-like structure that is present in the three-dimensional space and merges three-dimensional models of the line-like structures that are present in the three-dimensional space.
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公开(公告)号：US20210158016A1
公开(公告)日：2021-05-27
申请号：US17048083
申请日：2019-04-16
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Yasuhiro YAO , Hitoshi NIIGAKI , Ken TSUTSUGUCHI , Tetsuya KINEBUCHI
Abstract: A large-scale point cloud having no limitation on the range or the number of points is set as an object, and labels are attached to the points constituting the object regardless of the type of object.
A three-dimensional point cloud label learning apparatus 10A includes a ground-based height calculation unit that receives a three-dimensional point cloud and a ground surface height as inputs and outputs a three-dimensional point cloud with a ground-based height, an intensity-RGB conversion unit that receives the three-dimensional point cloud with the ground-based height as an input and outputs an intensity-RGB converted three-dimensional point cloud with the ground-based height, a supervoxel clustering unit that receives the intensity-RGB converted three-dimensional point cloud with the ground-based height, a point cloud label for learning, and a clustering hyperparameter as inputs and outputs supervoxel data with a correct answer label, and a deep neural network learning unit that receives the supervoxel data with the correct answer label and a deep neural network hyperparameter as inputs and outputs a learned deep neural network parameter.-
公开(公告)号：US20220392193A1
公开(公告)日：2022-12-08
申请号：US17775837
申请日：2019-11-11
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Yasuhiro YAO , Hitoshi NIIGAKI , Shingo ANDO , Jun SHIMAMURA
IPC: G06V10/762 , G06V10/77 , G06V10/82
Abstract: A clustering unit (101) divides an input three-dimensional point cloud into a plurality of clusters and outputs cluster data, a surrounding point sampling unit (102) extracts, for each of the plurality of clusters, a surrounding three-dimensional point cloud present within a predetermined distance of the cluster based on the three-dimensional point cloud and the cluster data, a learning unit (103) receives, as inputs, extended cluster data including information on a three-dimensional point cloud included in each cluster obtained by the division and information on the extracted surrounding three-dimensional point cloud and a correct answer label indicative of an object to which the three-dimensional point cloud included in each cluster belongs, and learns a parameter of a DNN for estimating a label of each cluster from the extended cluster data, and an estimation unit (104) inputs the extended cluster data related to the cluster of which the label is unknown to the DNN of which the parameter is trained to estimate the label of each cluster.
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Patent Agency Ranking
公开(公告)号：US20220058307A1
公开(公告)日：2022-02-24
申请号：US17413868
申请日：2019-12-03
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Masaki WAKI , Hitoshi NIIGAKI , Hiroaki TANIOKA , Ryoichi KANEKO , Gen KOBAYASHI , Kazuya ANDO
Abstract: An object of the present invention is to provide an equipment state detecting device, an equipment state detecting method, and a program that can create a 3D model of a cable based on three-dimensional coordinates acquired using a laser scanner or the like, and precisely estimate the tension for the entirety of the cable even if the entirety of the cable is not three-dimensionally modeled in the cable model. An equipment state detecting device of the present invention creates a 3D model of a cable based on three-dimensional coordinates acquired using a laser scanner or the like, acquires a sag and a straight line connecting ends of the 3D model based on the 3D model, and calculates the tension of the cable using a known cable load per unit length.
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公开(公告)号：US20230260216A1
公开(公告)日：2023-08-17
申请号：US17608735
申请日：2019-05-08
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Hitoshi NIIGAKI , Yasuhiro YAO , Shingo ANDO , Kana KURATA , Atsushi SAGATA
CPC classification number: G06T19/00 , G06T7/0002 , G06T2219/004 , G06T2207/10028 , G06T2210/56 , G06T2200/24 , G06T2207/20092
Abstract: Annotation can be easily performed on a three-dimensional point cloud and a working time can be reduced. An interface unit 22 displays a point cloud indicating a three-dimensional point on an object, and receives designation of a three-dimensional point indicating an annotation target object and designation of a three-dimensional point not indicating the annotation target object. A candidate cluster calculation unit 32 calculates a value of a predetermined evaluation function indicating a likelihood of a point cloud cluster being the annotation target object based on the designation of a three-dimensional point for point cloud clusters obtained by clustering the point clouds. A cluster selection and storage designation unit 34 causes the interface unit 22 to display the point cloud clusters in descending order of the value of the evaluation function, and receives a selection of a point cloud cluster to be annotated. An annotation execution unit 36 executes annotation indicating the annotation target object for each three-dimensional point included in the selected point cloud cluster.
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公开(公告)号：US20220222933A1
公开(公告)日：2022-07-14
申请号：US17612373
申请日：2019-05-23
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Yasuhiro YAO , Hitoshi NIIGAKI , Kana KURATA , Kazuhiko MURASAKI , Shingo ANDO , Atsushi SAGATA
IPC: G06V10/82 , G06V10/762 , G06V10/40 , G06N3/08
Abstract: A three-dimensional point cloud label learning and estimation device includes: a clustering unit that clusters a three-dimensional point cloud into clusters; a learning unit that makes a neural network learn to estimate a label corresponding to an object to which points contained in each of the clusters belong; and an estimation unit that estimates a label for the cluster using the neural network learned at the learning unit. In the three-dimensional point cloud label learning and estimation device, the neural network uses a total sum of sigmoid function values (sum of sigmoid) when performing feature extraction on the cluster.
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公开(公告)号：US20220215572A1
公开(公告)日：2022-07-07
申请号：US17608963
申请日：2019-05-08
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Hitoshi NIIGAKI , Yasuhiro YAO , Masaaki INOUE , Tomoya SHIMIZU , Yukihiro GOTO , Shigehiro MATSUDA , Ryuji HONDA , Hiroyuki OSHIDA , Kana KURATA , Shingo ANDO , Atsushi SAGATA
Abstract: Provided is a point cloud analysis device that curbs a decrease in model estimation accuracy due to a laser measurement point cloud. A clustering unit (30) clusters a point cloud representing a three-dimensional point on an object obtained by a measurement unit mounted on a moving body and performing measurement while scanning a measurement position, within a scan line, to obtain a point cloud cluster. A central axis direction estimation unit (32) estimates a central axis direction based on the point cloud cluster. A direction-dependent local effective length estimation unit (34) estimates a local effective length based on an estimated central axis direction and an interval of scan lines, the local effective length being a length when a length of projection of the point cloud cluster in a central axis direction for each of the point cloud clusters is interpolated by an amount of a loss part of the point cloud.
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公开(公告)号：US20220198690A1
公开(公告)日：2022-06-23
申请号：US17425916
申请日：2020-01-27
Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
Inventor： Yasuhiro YAO , Shingo ANDO , Kana KURATA , Hitoshi NIIGAKI , Atsushi SAGATA
Abstract: Dense depth information can be generated using only a monocular image and sparse depth information.
A depth hyper-resolving apparatus 100 includes: an input data processing unit 22 that outputs a hierarchical input image and hierarchical input depth information by resolution conversion in accordance with a predetermined number of tiers for an input image and input depth information; a depth continuity estimation unit 24 that derives hierarchical estimated depth continuity based on the hierarchical input image; a depth continuity mask deriving unit 26 that outputs a hierarchical depth continuity mask representing values of locations depending on whether a depth is continuous based on the hierarchical input image and the hierarchical estimated depth continuity; and a cost function minimization unit 30 that derives hyper-resolved depth information to minimize a cost function expressed by using the hierarchical input depth information, the hierarchical depth continuity mask, and the hyper-resolved depth information.
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