Abstract: To extract a feature advantageous for classification and correlation by using the information difficult to be acquired even when it is impossible to acquire the information difficult-to-be-acquired from all individuals. Sub-information input device inputs information difficult to be acquired and accumulates the inputted sub-information. Main information input device inputs information easy to be acquired as main information, and accumulates the inputted main information. Sub-information selection device evaluates a category attribution degree of each sub-information accumulated and selects the sub-information of a high category attribution degree. The correlation feature extraction device uses the sub-information selected by the sub-information selection device as the feature extraction filter, and extracts a feature corresponding to the main information from a correlation between the main information and the sub-information.

Abstract: The purpose is to execute the matching of a data after state change from a data before state change, or the matching of a data before state change from a data after state change. The component analyzing unit realized by software analyzes an input data by using a configuration component of a selected state-specific database and sends the configuration component coefficient to the component coefficient conversion unit. The component coefficient conversion unit converts the sent configuration component coefficient into the configuration component coefficient corresponding to the state-specific database which is not selected and sends it to the state change data generation unit. The state change data generation unit generates the state change data by using the sent configuration component coefficient and the configuration component of the corresponding state-specific database. The matching unit matches the state change data and the registration data accumulated in the matching data accumulating unit.

Abstract: A technique for applying a feature of a side attribute to an original image while keeping a principal feature. An image accumulating unit stores images classified into categories per the age or sex. A merging unit selects a category in accordance with an input category. A matching unit matches the input image and each of images included in the selected category with each other, and selects the image having highest degree of similarity. The merging unit merges the input image and the selected image by carrying out the weighted average and so on, and generates and outputs a merged image.

Abstract: A face image synthesis apparatus includes a storage device (2) and an arithmetic processing unit (1). The storage device (2) stores a plurality of face images and a plurality of feature points including an origin. The plurality of feature points are set to each of the plurality of face images. The arithmetic processing unit (1) generates a plurality of deformed face images by deforming the plurality of face images so that the origin and the other feature points thereof are matched to each other and generates a synthesized face image from the deformed face images.

Abstract: A 3D shape estimation system has a storage device, a relative shape analysis module, a feature point location search module and an absolute shape analysis module. The storage device stores first and second learning data which represent illumination bases and 3D shapes of objects, respectively. The relative shape analysis module calculates an “illumination basis” of an object based on a 2D image of the object and the first learning data, calculates a “relative shape function” that is partial differential of a “shape function” indicating a 3D shape of the object from the illumination basis, and outputs a relative shape data indicating the relative shape function. The feature point location search module extracts a plurality of feature points from the input 2D face image based on the 2D image and the relative shape data, and outputs a feature point location data indicating locations of the feature points.

Abstract: A data collating system includes an acquiring unit 20 configured to acquire data of a target object for collation as an input data 101; and a data collating unit 10 configured to store an original data 102A of an object input from a registering unit 30 and a status data 102A showing a status of the object, which are related to each other, and generate a status change data 106 corresponding to another status based on the original data 101A. The data collating unit collates the input data 101 with the status change data 106, transmits a collation result data 108 to a collation result output unit 40, and outputs the collation result.

Abstract: A shape deformation encoding device includes: a calculation unit for calculating a difference data between a pre-deformation shape data which represents a shape of an object before shape change and a post-deformation shape data which represents a shape of the object after shape change; and a determination unit for determining an action area on which the shape change of the object is arisen and an external force which is acted to the action area for the shape change, based on the pre-deformation shape data and the difference data. The action area includes a plurality of small areas, each of the plurality of small areas includes a plurality of control points, and the external force is calculated as an external force required to deform the plurality of small areas from before to after the shape change independently based on the physical model structure of each of the plurality of small areas.

Abstract: An image pickup apparatus comprises a space-frequency characteristic pattern irradiating section which irradiates a visible light which has passed through an optical filter having a predetermined space-frequency characteristic to the target object; a camera; a difference image generating section which generates a difference image between a first and a second image each picked up by the camera when the visible light is irradiated or not irradiated from the space-frequency characteristic pattern irradiating section; a space-frequency domain transforming section which transforms the generated difference image to a space-frequency domain to acquire a space-frequency characteristic of each pixel of the difference image; a space-frequency pattern collating section which collates the space-frequency characteristic of each acquired pixel with the space-frequency characteristic of the optical filter; and a subject image generating section which generates a subject image from which the subject area has been extracted b

Abstract: In an image processing system having a primary image pickup device and a plurality of reference image pickup devices, a feature region consisting of a plurality of feature segments each defined by a pair of feature points is extracted from a primary image. Subsequently, a correspondence point candidate of each of the feature points is extracted from each of the reference images. Based on the feature points and the correspondence point candidate of each of the feature points for each of the reference images, three-dimensional coordinates corresponding to the feature points are calculated, and the feature region is extracted as a target object from the primary image based on the feature points and the three-dimensional coordinates corresponding to the feature points for each of the reference images.

Abstract: A main image pickup section for picking up a main image and two or more subsidiary image pickup sections for picking up subsidiary images are used to shoot a subject. A 3-D object on which a predetermined pattern is drawn is also shot by the same image pickup sections, and parameters representing relative positions and attitudes of the image pickup sections are obtained using the images of the 3-D object. Feature points are extracted from each of the main image and the subsidiary images, and 3-D coordinates corresponding to each feature point in the main image are determined using the parameters and the feature points in the subsidiary images. Subsequently, judgment is executed and each of the feature points in the main image is accepted if the 3-D coordinates is within a designated 3-D space domain. Subsequently, subject outline points are extracted from the accepted feature points. Then, part of the main image which is surrounded by the subject outline points is extracted as the subject image.

Abstract: An image processor comprising an image pickup portion to take in an image of an object, a reference point extracting portion that extracts a reference point to be used in object extraction from images taken by the image pickup portion,a corresponding point detecting portion that detects a corresponding point in other images, a three dimensional coordinates value calculating portion that calculates a three dimensional coordinates value of an object by using the absolute position and posture parameters calculated by using image of a reference solid and coordinates values of reference point and corresponding point, a contour point extracting portion that extracts a contour point to show contour of an object on the basis of coordinate values of reference point and three dimensional coordinate values, and an object display control portion that extracts an image of the object from images photographed by the image pickup portion based on coordinates value of contour point and displays it on a display device.

Abstract: In a three-dimensional position detecting apparatus, a perspective projection image sensing unit takes a perspective projection image of a target object having plural feature points P.sub.0, P.sub.1, . . . , and an orthographic projection image sensing unit takes an orthographic projection image of the target object having the plural feature points. A two-dimensional coordinate acquiring unit acquires the two-dimensional coordinates of feature points in the perspective projection image, and the two-dimensional coordinates of feature points in the orthographic projection image. A camera parameter calculating unit calculates camera parameters with the two-dimensional coordinates of the feature points obtained by the two-dimensional coordinate acquiring unit.