Panasonic Intellectual Property Management Co., Ltd.

Panasonic Corporation

Matsushita Electric Industrial Co., Ltd.

Panasonic Intellectual Property Corporation of America

Hiroya Kusaka

Taro Imagawa

Akihiro Noda

Yuki Maruyama

Shigeo Sakaue

Takashi Sakaguchi

Masaaki Nakayama

Michiharu Uematsu

Masamichi Ohara

Hideyuki Hashi

Kenichi Hayashi

Atsuo Ochi

Shunsuke Yasugi

Teruyuki Takizawa

Kazuhiko Ishimaru

Yasutoshi Yamamoto

Takayuki Hayashi

Tomoaki Tsutsumi

Masanobu Tanaka

Kazutaka Furuta

An information processing method includes: obtaining training images generated by a camera shooting a target point and training parameters related to a position/orientation of the camera when shooting the training images; generating, using the training parameters as inputs, a model that outputs a first displacement amount by which a target block corresponding to the target point displaces from a reference position in the training images; obtaining measurement images generated by the camera shooting the target point and measurement parameters related to the position/orientation of the camera when shooting the measurement images; obtaining a second displacement amount, output by inputting the measurement parameters into the model, by which a target block corresponding to the target point appearing in the measurement images displaces from a reference position in the measurement images; and outputting a displacement obtained by subtracting the second displacement amount from displacement of the target block in the measurement images.

Information processing method, information processing device, and information processing system for measuring displacement in a structure

A measurement method, which is performed by a measurement device that measures a displacement of a target object, includes: receiving designation of a designation point on a first image that includes the target object; setting a plurality of set points, based on the designation point; identifying a direction of a line that connects two of the plurality of set points; generating a second image by rotating the first image, the second image being an image in which the identified direction of the line is horizontal or vertical; setting, in the second image, a measurement region that partially includes the line; and measuring the displacement of the target object in the measurement region, the displacement being a displacement in a direction orthogonal to the line.

Measurement method and measurement device

A conversion parameter calculation method includes: obtaining, from a first image capturing device, first image data obtained by the first image capturing device capturing an image of an object; obtaining, from a second image capturing device, second distance data indicating a distance to the object, and second image data obtained by the second image capturing device capturing an image of the object; obtaining displacement direction information indicating a direction of a displacement of the object in three dimensions; associating positions on the object in the first image data and the second image data; estimating a position of the first image capturing device; calculating first distance data indicating a distance from the first image capturing device to the object; and calculating a conversion parameter for converting a pixel displacement amount of the object into the actual displacement amount, using the first distance data and the displacement direction information.

Conversion parameter calculation method, displacement amount calculation method, conversion parameter calculation device, and displacement amount calculation device

An imaging parameter output method is a method of outputting an imaging parameter of an imaging device that captures an image for measuring a displacement representing a movement of an object. The imaging parameter output method includes: obtaining object information identifying the object, and a geometric imaging condition for imaging the object; calculating the imaging parameter including a candidate imaging area for placing the imaging device and the accuracy in measuring the displacement in the candidate imaging area, based on the object information and the geometric imaging condition, without imaging the object using the imaging device; and outputting the imaging parameter.

Imaging parameter output method and imaging parameter output device

An axle load measuring apparatus includes a displacement calculator, a storage, and an axle load calculator. The displacement calculator detects displacements of positions on a road caused by an axle load using a captured image of the road and a vehicle thereon. When a certain amount of load is applied to a predetermined position of the road, the storage stores a displacement function representing shape information of a spatial distribution of a displacement of the road originated from the predetermined position. The axle load calculator calculates the axle load based on the displacements of the positions and the displacement function.

Axle load measuring apparatus and axle load measuring method

A detection device includes an acquirer that acquires a video of each of a plurality of bearings of a structure including the plurality of bearings, an extractor that extracts a dynamic feature corresponding to a plurality of degrees of freedom of each of the plurality of bearings based on the video, and an identifier that identifies, among the plurality of bearings, a bearing whose dynamic feature fails to match a dynamic feature of one or more other bearings of the plurality of bearings.

Bearing displacement detection device and method

A conversion parameter calculation method includes: obtaining, from an image capturing device, image data obtained by the image capturing device capturing an image of an object having attached thereto a marker with which specific coordinates are detectable; obtaining displacement direction information indicating a direction of a displacement of the object, the direction crossing an image capturing surface of the image capturing device; detecting specific coordinates, based on the marker included in the image data; estimating a position of the image capturing device, based on a result of the detection; calculating distance data indicating a distance from the image capturing device to the object, based on the position of the image capturing device; and calculating, using the distance data and the displacement direction information, a conversion parameter for converting a pixel displacement amount of the object into an actual displacement amount.

A prediction device for predicting the growth direction of a crack that occurs in a subject includes: an obtainer that obtains video of the subject; a derivation unit that derives displacement of each of a plurality of regions in the obtained video; a selector that selects, from among the plurality of regions, two or more regions each having displacement similar to displacement of a reference region included in the plurality of regions; and an identification unit that identifies, as the growth direction, the longitudinal direction of a collective region made up of the two or more selected regions.

Prediction device for predicting a growth direction of a crack in a subject and prediction method

An inspection device that inspects a structure with a crack, including: an obtainer that obtains images of the structure captured at mutually different times while the structure is subjected to varying loads; a crack detector that detects a crack on a surface of the structure in each image; a motion estimator that divides each image into blocks having a predetermined size, and derives motion vectors of the blocks based on a positional relation between a position of each block relative to a reference in a first image and a position of each block relative to the reference in a second image, the reference being a tip of the crack detected, the first and second images being included in the images; and an inspector that determines safety of the structure based on a difference between ones of the motion vectors of symmetric positions with respect to the crack.

Inspection device and inspection method

A load meter includes a detector, a storage unit, and a load calculator. The detector detects, by using a captured image obtained by capturing a road and a vehicle present on the road, a displacement amount in the captured image, the displacement amount corresponding to displacement caused on the road by application of a load of the vehicle. The storage unit stores information indicating a relation between the load and the displacement amount. The load calculator calculates the load based on the displacement amount and the information.

Load meter and load measurement method

A displacement measurement device includes: an obtainer that obtains a first image which contains a subject and a second image which contains the subject; a generator that generates M template images which contain the subject and which have noise from the first image and generates M target images which contain the subject and which have noise from the second image, M being an integer of 2 or higher; a hypothetical displacement calculator that calculates M hypothetical displacements of the subject from the M template images and the M target images; and a displacement calculator that calculates a displacement of the subject by performing statistical processing on the M hypothetical displacements.

Displacement measurement device and displacement measurement method

A displacement measurement device includes: a first machine learning model trained to generate, from one image which contains a subject and has noise, at least one image which contains the subject and which has noise or has had noise removed; a first obtainer that obtains a first image which contains the subject and has noise and a second image which contains the subject and has noise; a first generator that, using the first machine learning model, generates M template images containing the subject from the first image and generates M target images containing the subject from the second image, M being an integer of 2 or higher; a hypothetical displacement calculator that calculates M hypothetical displacements of the subject from the M template images and the M target images; and a displacement calculator that calculates a displacement of the subject by performing statistical processing on the M hypothetical displacements.

An information presentation method according to the present disclosure includes: acquiring two or more monochrome images obtained by image-capturing a structure using a monochrome camera and one or more first color images obtained by image-capturing the structure using a color camera, the one or more first color images having a less amount of information than an amount of information of the two or more monochrome images; detecting a displacement that indicates a movement of the structure based on the two or more monochrome images; generating presentation information that includes one or more second color images that present information that indicates the displacement based on the two or more monochrome images and the one or more first color images; and outputting the presentation information.

Information presentation methods

A lift-up determining device includes a detector and a determination unit. The detector acquires a captured image including a tire on an axle of a vehicle and detects the tire from the captured image. The determination unit determines, based on a detection result by the detector, whether the axle is lifted up.

Lift-up determining device and lift-up determining method

A monitoring system includes an axle weight measurer and a state estimator. The axle weight measurer detects a surface displacement of a road from a first captured image obtained by imaging the road when a vehicle passes at a predetermined spot of a structure having the road that the vehicle passes, and calculates an axle weight of the vehicle from the surface displacement and a displacement coefficient of the road. The state estimator generates an axle weight distribution from the axle weight calculated by the axle weight measurer, and estimates a deterioration degree of the structure, using the axle weight distribution.

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Hyogo, Japan

Hiroya Kusaka