Abstract:
An apparatus includes a first acquisition unit configured to acquire main object information specifying a main object in generation of a layout image, a second acquisition unit configured to acquire object correlation information specifying an object having a correlation with the main object, an extraction unit configured to extract at least one image including the main object and at least one image including the object having the correlation with the main object from a plurality of images based on the acquired main object information and the acquired object correlation information acquired, and a generation unit configured to generate, using a layout template, a layout image in which the at least one image extracted by the extraction unit and including the main object and the at least one image extracted by the extraction unit and including the object having the correlation with the main object are laid out therein.
Abstract:
A method includes a state determination step of determining the quality of an object in image data, an extraction step of extracting feature information from the object, and a registration step of registering, in a dictionary, the feature information extracted in the extraction step. In the registration step, when the quality of the object determined in the determination step is lower than a predetermined reference, registration of the feature information of the object in the dictionary by the registration step is not performed.
Abstract:
This invention provides a technique which can enhance personal recognition precision in personal recognition processing of a face in an image. To this end, a management unit classifies feature patterns each including feature information of a plurality of parts of a face region of an object extracted from image data, and manages the feature patterns using a dictionary. A segmenting unit determines whether or not feature information of each part of the face region of the object is segmented, and segments the feature information of the part of interest into a plurality of feature information as new feature information. A registration unit registers a feature pattern as a combination of the new feature information of the part of interest and feature information of parts other than the part of interest in the dictionary as a new feature pattern of the object.
Abstract:
Images of a layout target for a template are acquired. The plurality of acquired images are edited using editing processing corresponding to a category corresponding to a layout. The edited images are arranged on the template corresponding to the category.
Abstract:
Images of a layout target for a template are acquired. The plurality of acquired images are edited using editing processing corresponding to a category corresponding to a layout. The edited images are arranged on the template corresponding to the category.
Abstract:
An image processing apparatus includes an image data acquisition unit to acquire image data by optically reading a document. A frequency distribution acquisition unit acquires a first frequency distribution of luminances from the image data acquired by the image data acquisition unit. A generation unit generates a second frequency distribution of luminances of a background of the document, by using a maximum frequency of the first frequency distribution as a maximum frequency of the second frequency distribution of luminances of the background of the document. An acquisition unit acquires information indicating a degree of deviation of the second frequency distribution from the first frequency distribution. A correction unit corrects the second frequency distribution based on the information indicating the degree of deviation acquired by the acquisition unit.
Abstract:
An apparatus includes an acquisition unit configured to acquire at least one image group including at least one image; a creating unit configured to create a layout candidate by laying out images included in an image group that has been acquired by the acquisition unit; an evaluating unit configured to evaluate the layout candidate created by the creating unit, based on individual evaluation of each of the images in accordance with a feature of a subject in the images that have been laid out in layouts; and an output unit configured to output the layout candidate created by the creating unit, at a predetermined output size. The feature of the subject in the images includes a size of the subject in the image identified by an output size of the layout candidate output by the output unit.
Abstract:
An apparatus includes a first acquisition unit configured to acquire main object information specifying a main object in generation of a layout image, a second acquisition unit configured to acquire object correlation information specifying an object having a correlation with the main object, an extraction unit configured to extract at least one image including the main object and at least one image including the object having the correlation with the main object from a plurality of images based on the acquired main object information and the acquired object correlation information acquired, and a generation unit configured to generate, using a layout template, a layout image in which the at least one image extracted by the extraction unit and including the main object and the at least one image extracted by the extraction unit and including the object having the correlation with the main object are laid out therein.
Abstract:
An apparatus extracts feature information from an object of image data. The apparatus registers the extracted feature information in a dictionary. The apparatus refers to the dictionary and determines a similarity between feature information registered in the dictionary and the extracted feature information. The apparatus does not use, of feature information to be registered in the dictionary, feature information not satisfying a predetermined evaluation criterion in similarity determination.
Abstract:
This invention provides a technique which can enhance personal recognition precision in personal recognition processing of a face in an image. To this end, a management unit classifies feature patterns each including feature information of a plurality of parts of a face region of an object extracted from image data, and manages the feature patterns using a dictionary. A segmenting unit determines whether or not feature information of each part of the face region of the object is segmented, and segments the feature information of the part of interest into a plurality of feature information as new feature information. A registration unit registers a feature pattern as a combination of the new feature information of the part of interest and feature information of parts other than the part of interest in the dictionary as a new feature pattern of the object.