Abstract: An apparatus includes a memory and a processor connected to the memory, wherein the processor acquires a plurality of images of an installed rebar group that have been captured while an image capturing region is being moved in a direction intersecting the rebar group, detects a tracking target from a first edge portion, and correlates, when the processor has detected the tracking target from the first edge portion, either of a detection image that is an image of the detected tracking target or a captured image captured after the detection or alternative information generated on the basis of the detection image or the captured image with identification information for identifying a rebar belonging to the rebar group and located within a predetermined range from the tracking target, and records the image, or alternative information correlated with the identification information in a recording apparatus.

Abstract: According to an embodiment, an arithmetic method includes accepting an input of image data, detecting a representative position of a characteristic portion from the image data the input of which has been accepted, acquiring a user instructed position in the image data, calculating a position difference indicating a difference between the detected representative position and the acquired user instructed position, and selecting the representative position of the characteristic portion as a target portion if the calculated position difference is smaller than a predetermined first threshold and selecting the user instructed position as a target portion if the position difference is not smaller than the first threshold.

Abstract: An image acquisition device includes a computer configured to: acquire image data; store a plurality of parameter sets each constituted of a plurality of parameters including photographing conditions and developing conditions; obtain a change from a reference parameter for one of the parameters relating to the photographing conditions, the change being made by a user at the time of acquisition of the image data; extract the parameter sets remaining after excluding the parameter sets involving the change in the changed parameter in a case where the change in the parameter has been obtained; and develop, using the extracted parameter sets, the acquired image data.

Abstract: An image acquisition device includes a computer configured to: acquire image data; store a plurality of parameter sets each constituted of a plurality of parameters including photographing conditions and developing conditions; obtain a change from a reference parameter for one of the parameters relating to the photographing conditions, the change being made by a user at the time of acquisition of the image data; extract and present the parameter sets involving changes in the same direction as the change in the changed parameter so as to allow the user to select one of those parameter sets in a case where the change in the parameter is obtained; and develop the acquired image data by using the parameter set selected by the user.

Abstract: According to an embodiment, an arithmetic method includes accepting an input of image data, detecting a representative position of a characteristic portion from the image data the input of which has been accepted, acquiring a user instructed position in the image data, calculating a position difference indicating a difference between the detected representative position and the acquired user instructed position, and selecting the representative position of the characteristic portion as a target portion if the calculated position difference is smaller than a predetermined first threshold and selecting the user instructed position as a target portion if the position difference is not smaller than the first threshold.

Abstract: A server apparatus is configured to communicate with a photographing apparatus. Image date is recorded in a database. An evaluation acquisition unit acquires evaluation information and evaluated image data. A first feature amount extraction unit extracts a first feature amount from at least one of the evaluation information and the evaluated image data. A reception unit receives temporarily photographed image data from the photographing apparatus. A second feature amount extraction unit extracts a second feature amount from the temporarily photographed image data. A retrieval unit detects image data based on the first feature amount and the second feature amount. A parameter acquisition unit acquires a photographing parameter from the image data detected by the retrieval unit. A transmission unit transmits the photographing parameter to the photographing apparatus.

Abstract: An imaging apparatus includes an object database, a composition database, an imaging unit, a determination unit, a search unit, a priority setting unit, and a display. The determination unit extracts an image feature amount from a photographed image data, and determines a kind of an object of the photographed image data, based on data stored in the object database. The search unit detects composition assisting information corresponding to the photographed image data from the composition database, based on the kind of the object and data stored in the composition database. The priority setting unit extracts characteristic information and determines presentation priority based on characteristic information differences. The display displays the composition assisting information based on the priority.

Abstract: An imaging apparatus includes an object database, a composition database, an imaging unit, a determination unit, a search unit, a priority setting unit, and a display. The determination unit extracts an image feature amount from a photographed image data, and determines a kind of an object of the photographed image data, based on data stored in the object database. The search unit detects composition assisting information corresponding to the photographed image data from the composition database, based on the kind of the object and data stored in the composition database. The priority setting unit extracts characteristic information and determines presentation priority based on characteristic information differences. The display displays the composition assisting information based on the priority.

Abstract: A server apparatus is configured to communicate with a photographing apparatus. Image date is recorded in a database. An evaluation acquisition unit acquires evaluation information and evaluated image data. A first feature amount extraction unit extracts a first feature amount from at least one of the evaluation information and the evaluated image data. A reception unit receives temporarily photographed image data from the photographing apparatus. A second feature amount extraction unit extracts a second feature amount from the temporarily photographed image data. A retrieval unit detects image data based on the first feature amount and the second feature amount. A parameter acquisition unit acquires a photographing parameter from the image data detected by the retrieval unit. A transmission unit transmits the photographing parameter to the photographing apparatus.

Abstract: A method of compiling an image database for a three-dimensional object recognition including the steps of: when a plurality of images each showing an object from different viewpoint are inputted, extracting local features from each of the images, and expressing the local features using feature vectors; forming sets of the feature vectors, each set representing a same part of the object from a series of the viewpoints, and generating subspaces, each subspace representing a characteristic of each set; and storing each subspace to the image database with an identifier of the object to perform a recognition process that is realized by the steps of: when at least one image of an object is given as a query, extracting query feature vectors; determining the subspace most similar to each query feature vector; and executing a counting process to the identifiers to retrieve an object most similar to the query.

Abstract: An image retrieval method comprising: a step of extracting at least one query feature vector from a query image on which a subject of the image retrieval is captured, the query feature vector representing a local feature of the query image; a step of accessing an image data base in which a plurality of reference images are stored previously, each reference image being stored in conjunction with learning images generated therefrom and reference feature vectors representing local features of the reference image and the learning images; a comparing step of comparing the query feature vector with the reference feature vectors stored in conjunction with each reference image using an approximate nearest neighbor search to find a reference feature vector approximately nearest to the query feature vector; and a selecting step of selecting a reference image with which the found reference feature vector is stored in conjunction from the reference images as a retrieval result wherein: the learning image is generated by

Abstract: A method for creating an image database comprising an extraction step of extracting reference feature vectors from a reference image which should be compared with a retrieval query image for object recognition, the reference feature vectors corresponding to local features at different positions of the reference image and representing the position and characteristics of each of the local features as a vector position, vector length, and a vector direction, a clustering step of creating a plurality of clusters consisting of different reference feature vectors in such a manner that each reference vector belongs to any of the plurality of clusters, a selection step of selecting the representative vector of the clusters from among the reference feature vectors of each of the clusters, and a step of associating the representative vector with the reference image and registering the representative vector associated therewith in the image database for the object recognition, wherein, in the clustering step, each of th

Abstract: A method of compiling an image database for a three-dimensional object recognition including the steps of: when a plurality of images each showing an object from different viewpoint are inputted, extracting local features from each of the images, and expressing the local features using feature vectors; forming sets of the feature vectors, each set representing a same part of the object from a series of the viewpoints, and generating subspaces, each subspace representing a characteristic of each set; and storing each subspace to the image database with an identifier of the object to perform a recognition process that is realized by the steps of: when at least one image of an object is given as a query, extracting query feature vectors; determining the subspace most similar to each query feature vector; and executing a counting process to the identifiers to retrieve an object most similar to the query.

Abstract: An image retrieval method comprising: a step of extracting at least one query feature vector from a query image on which a subject of the image retrieval is captured, the query feature vector representing a local feature of the query image; a step of accessing an image data base in which a plurality of reference images are stored previously, each reference image being stored in conjunction with learning images generated therefrom and reference feature vectors representing local features of the reference image and the learning images; a comparing step of comparing the query feature vector with the reference feature vectors stored in conjunction with each reference image using an approximate nearest neighbor search to find a reference feature vector approximately nearest to the query feature vector; and a selecting step of selecting a reference image with which the found reference feature vector is stored in conjunction from the reference images as a retrieval result wherein: the learning image is generated by

Abstract: A method for creating an image database comprising an extraction step of extracting reference feature vectors from a reference image which should be compared with a retrieval query image for object recognition, the reference feature vectors corresponding to local features at different positions of the reference image and representing the position and characteristics of each of the local features as a vector position, vector length, and a vector direction, a clustering step of creating a plurality of clusters consisting of different reference feature vectors in such a manner that each reference vector belongs to any of the plurality of clusters, a selection step of selecting the representative vector of the clusters from among the reference feature vectors of each of the clusters, and a step of associating the representative vector with the reference image and registering the representative vector associated therewith in the image database for the object recognition, wherein, in the clustering step, each of th

Abstract: An information presentation system includes an imaging unit, a peripheral information acquisition unit which acquires peripheral information, a storage unit which stores registered information, an analytic basic information construction unit which constructs analytic basic information from the registered information stored in the storage unit, on the basis of the peripheral information acquired in the peripheral information acquisition unit, a pertinent information acquisition unit which acquires information pertinent to the image from the image obtained from the imaging unit and the analytic basic information obtained from the analytic basic information construction unit, and a presentation unit which presents the pertinent information acquired in the pertinent information acquisition unit.

Abstract: In a feature matching method for recognizing an object in two-dimensional or three-dimensional image data, features in each of which a predetermined attribute in the two-dimensional or three-dimensional image data takes a local maximum and/or minimum are detected, and features existing along edges and line contours from the detected features are excluded. Thereafter, the remaining features are allocated to a plane, some features are selected from the allocated features by using local information, and feature matching for the selected features being set as objects is performed.

Abstract: An information presentation method is to photograph an object by use of an image input device and display related information corresponding to the object on the object in a display screen or the periphery of the object in the display screen. The related information of the object is expressed by the contents of expression of a plurality of two-dimensional markers set on the object or the periphery of the object and the plurality of two-dimensional markers correspond to any one of a plurality of information series.

Abstract: Image information is input by an image input unit, a marker is extracted from an image of the input image information by a marker detector, a position of the extracted marker in the image is detected by a position/posture detector, and the difference between indicators extracted from images is judged. At this time, the position/posture detector is provided with a judgment condition based on the position of each marker, as a judgment condition that is at least selectively applied.

Abstract: An image processing device comprises an image acquisition apparatus configured to acquire an image of an object, a feature extraction unit configured to extract a feature portion from a visual field of the image acquired by the image acquisition apparatus, a weighting section configured to calculate a weight in accordance with extraction conditions of the feature portion extracted by the feature extraction unit to weight the feature portion, and a position orientation obtaining section configured to obtain a position and an orientation of the image acquisition apparatus on a reference coordinate system from the feature portion weighted by the weighting section.