Abstract:
An image processing apparatus includes an input unit configured to input an image, a determining unit configured to determine a foreground area and a background area in the image input by the input unit, an expansion unit configured to expand the foreground area determined by the determining unit, a calculating unit configured to calculate a feature amount of the foreground area expanded by the expansion unit, and a detecting unit configured to detect an object from the image using the feature amount.
Abstract:
An image processing apparatus includes an image input unit configured to input an image, a scanning unit configured to scan a detection window on the input image, a first discrimination unit configured to determine whether a pattern within the detection window is a subject based on a plurality of characteristic amounts obtained from within a first region among a plurality of regions within the detection window, and a second discrimination unit configured to determine, if it is determined that the pattern is not the subject by the first discrimination unit, whether the pattern is the subject based on a plurality of characteristic amounts obtained from a second region in which a probability that occlusion of the subject occurs is higher than that in the first region among the plurality of regions. Accordingly, a subject can be detected efficiently, and omissions of detection can be reduced.
Abstract:
An image processing apparatus includes a first detecting unit configured to detect an object based on an upper body of a person and a second detecting unit configured to detect an object based on a face of a person. The image processing apparatus determines a level of congestion of objects contained in an input image, selects the first detecting unit when the level of congestion is low, and selects the second detecting unit when the level of congestion is high. The image processing apparatus counts the number of objects detected by the selected first or second detecting unit from the image. Thus, the image processing apparatus can detect an object and count the number of objects with high precision even when the level of congestion is high and the objects tend to overlap one another.
Abstract:
An information processing apparatus for extracting a more appropriate representative frame image from moving image data that includes a plurality of frames of image data arranged in a time series includes: an input unit configured to input moving image data; a detecting unit configured to detect a frame image, which includes an image similar to a prescribed image pattern; a tracking unit configured to detect a frame image, which includes an image similar to the image included in the detected frame image; a storage unit configured to store successive frame images that have been detected by the tracking unit; a splitting unit configured to split the moving image data into a plurality of time intervals; and an extracting unit configured to extract a representative frame image using different evaluation rules.
Abstract:
A plurality of collation patterns having different resolutions are generated from an original collation pattern which includes a plurality of local regions. Subject reliabilities for individual local regions are calculated based on local features of the local regions in the collation patterns having different resolutions. In accordance with the subject reliabilities for individual local regions, it is determined that the original collation pattern includes a specific image of a subject.
Abstract:
There are provided an image search apparatus, and an image search method, which make it easier for a user to reach an image desired to be searched, by rearranging images to which keywords matching an inputted search term are assigned, according to the importance of the keywords to the image desired to be searched, and a storage medium storing a program for executing the image control and search method. Keywords corresponding to images to be searched are searched for according to the inputted search terms, and images corresponding to the keywords searched are rearranged according to importance set for the keywords. The images are stored together with the keywords for which the importance has thus been determined. The images to which the keywords matching the inputted search term are rearranged in the order of the importance.
Abstract:
A recognition apparatus includes a calculation unit configured to calculate likelihood of each feature quantity based on the weighted distribution of the feature quantity extracted from a plurality of learning images, a correction unit configured, if a ratio of a learning image to a specific feature quantity is equal to or smaller than a predetermined ratio and a weight for the specific feature quantity is greater than a predetermined value, to correct the value of likelihood of the specific feature quantity to lower the value based on the distribution, a setting unit configured to set the likelihood corrected by the correction unit in association with a feature quantity, and a discrimination unit to extract a feature quantity from an input image and discriminate whether the input image includes a predetermined object based on the likelihood associated with the feature quantity.
Abstract:
An image processing apparatus includes an input unit configured to input an image, a determining unit configured to determine a foreground area and a background area in the image input by the input unit, an expansion unit configured to expand the foreground area determined by the determining unit, a calculating unit configured to calculate a feature amount of the foreground area expanded by the expansion unit, and a detecting unit configured to detect an object from the image using the feature amount.
Abstract:
An image processing apparatus includes a moving image input unit configured to input a moving image, an object likelihood information storage unit configured to store object likelihood information in association with a corresponding position in an image for each object size in each frame included in the moving image, a determination unit configured to determine a pattern clipping position where a pattern is clipped out based on the object likelihood information stored in the object likelihood information storage unit, and an object detection unit configured to detect an object in an image based on the object likelihood information of the pattern clipped out at the pattern clipping position determined by the determination unit.
Abstract:
An information processing apparatus for extracting a more appropriate representative frame image from moving image data that includes a plurality of frames of image data arranged in a time series includes: an input unit configured to input moving image data; a detecting unit configured to detect a frame image, which includes an image similar to a prescribed image pattern; a tracking unit configured to detect a frame image, which includes an image similar to the image included in the detected frame image; a storage unit configured to store the successive frame images in association with time information; a splitting unit configured to split the moving image data into a plurality of time intervals with starting time and end time of each of one or more image sequences; and an extracting unit configured to extract a representative frame image.