Abstract:
A multi-class identifier identifies a kind of an imager, and identifies in detail with respect to a specified kind of a group. The multi-class identifier includes: an identification fault counter providing the image for test that includes any of class labels to the kind identifiers so that the kind identifiers individually identify the kind of the provided image, and counting, for a combination of arbitrary number of kinds among the plurality of kinds, the number of times of incorrect determination in the arbitrary number of kinds that belongs to the combination; a grouping processor, for a group of the combination for which count result is equal to or greater than a predetermined threshold, adding a group label corresponding to the group to the image for learning that includes the class label corresponding to any of the arbitrary number of kinds that belongs to the group.
Abstract:
In an object searching apparatus for searching through a database of objects, an image pickup unit repeatedly shoots a subject with the optical axis moved to obtain plural pieces of image data. A distance from the image pickup unit to the subject is calculated based on the plural pieces of image data, and a main object of the subject is clipped from the obtained image data. A calculating unit calculates a real size of the main object of the subject based on a size of the clipped main object on the image data, the calculated distance from the image pickup unit to the subject and a focal length of the image pickup unit. A searching unit accesses the database to search for a sort of the main object of the subject, using the calculated real size of the main object.
Abstract:
In the present invention, a database has feature information stored in association with flower sample images flower names, leaf sample images, and images indicating attention points for narrowing down the flower names. An extracting section extracts flower sample images having a high similarity to the image of the imaged flower as candidate images by comparing feature information of the image of the imaged flower and feature information stored in the database. A control section causes the image of the imaged flower, the extracted candidate images, flower names corresponding to the candidate images, and attention points for narrowing down the candidate images to be arranged and displayed on a display section, and changes the candidate images to their respective leaf sample images for display. The control section also changes the candidate images to images indicating their respective attention points and causes them to be displayed on the display section.
Abstract:
A multi-class discriminating device for judging to which class a feature represented by data falls. The device has a first unit for generating plural first hierarchical discriminating devices for discriminating one from N, and a second unit for combining score values output respectively from the plural first hierarchical discriminating devices to generate a second hierarchical feature vector and for entering the second hierarchical feature vector to generate plural second hierarchical discriminating devices for discriminating one from N. When data is entered, the plural first hierarchical discriminating devices output score values, and these score values are combined together to generate the second hierarchical feature vector. When the second hierarchical feature vector is entered, the second hierarchical discriminating device which outputs the maximum score value is selected. The class corresponding to the selected second hierarchical discriminating device is discriminated as the class, into which the feature represented by the entered data falls.
Abstract:
The image acquisition unit 41 acquires an image including an object. By comparing information related to the shape of a relevant natural object that is included as the object in the target image acquired by the image acquisition unit 41, and information related to respective shapes of a plurality of types prepared in advance, at least one flower type for the natural object in question is selected. The secondary selection unit 43 then selects data of a representative image from among data of a plurality of images of different color, of the same flower type as prepared in advance, for each of at least one flower type selected by the primary selection unit 42, based on information related to color of the relevant natural object included as the object in the image acquired by the image acquisition unit 41.