Abstract: This rare earth magnet having high strength and high electrical resistance has a structure including an R—Fe—B-based rare earth magnet particles 18 which are enclosed with a high strength and high electrical resistance composite layer 12. The high strength and high electrical resistance composite layer 12 is constituted from a glass-based layer 16 that has a structure comprising a glass phase or R oxide particles 13 dispersed in glass phase, and R oxide particle-based mixture layers 17 that are formed on both sides of the glass-based layer 16 and contain an R-rich alloy phase 14 which contains 50 atomic % or more of R in the grain boundary of the R oxide particles.

Abstract: A pattern identification unit generation method of generating a pattern identification unit in which a weak discriminator array obtained by cascade-connecting a plurality of weak discriminators branches, and weak discriminator arrays are connected to respective arms after branching, evaluates based on a processing result obtained by inputting a set of evaluation data to the weak discriminator array whether or not a weak discriminator array after branching reaches the number of stages to be connected. The number of stages of weak discriminators to be connected without branching as the weak discriminator array is determined based on this evaluation result.

Abstract: An image processing method is provided for an image processing apparatus which executes processing by allocating a plurality of weak discriminators to form a tree structure having branches corresponding to types of objects so as to detect objects included in image data. Each weak discriminator calculates a feature amount to be used in a calculation of an evaluation value of the image data, and discriminates whether or not the object is included in the image data by using the evaluation value. The weak discriminator allocated to a branch point in the tree structure further selects a branch destination using at least some of the feature amounts calculated by weak discriminators included in each branch destination.

Abstract: In an image conversion method, a value which reflects the mutual relationship between the classes of pixel patterns each formed from a pixel classified as one of a plurality of classes and peripheral pixels is set as a converted value corresponding to each of the plurality of classes, a pixel of interest is sequentially selected from the input image, and a pixel pattern formed from the selected pixel of interest and a predetermined number of pixels around it is classified as one of the plurality of classes in accordance with a neighboring pattern obtained based on the relationship between the value of the pixel of interest and the values of peripheral pixels located at predetermined relative positions with respect to the pixel of interest. The value of the pixel of interest is converted into a converted value set for a class to which the pixel of interest has been classified.

Abstract: A learning apparatus for a pattern detector, which includes a plurality of weak classifiers and detects a specific pattern from input data by classifications of the plurality of weak classifiers, acquires a plurality of data for learning in each of which whether or not the specific pattern is included is given, makes the plurality of weak classifiers learn by making the plurality of weak classifiers detect the specific pattern from the acquired data for learning, selects a plurality of weak classifiers to be composited from the weak classifiers which have learned, and composites the plurality of weak classifiers into one composite weak classifier based on comparison between a performance of the composite weak classifier and performances of the plurality of weak classifiers.

Abstract: An image capturing unit acquires an image including an object. A state detection unit detects the state of the object in the image. An individual recognition processing unit determines one of a plurality of individual identification process modules in correspondence with the state detected by the state detection unit. The individual recognition processing unit executes, for the object in the image, an individual identification process by the determined individual identification process module.

Abstract: In an image within which a face pattern is detected, when a ratio of a skin color pixel is equal to or smaller than a first threshold value in a first region and a ratio of a skin color pixel is equal to or greater than a second threshold value in a second r region, the vicinity of the first region is determined to be a face candidate position at which the face pattern can exist. Face detection is carried out on the face candidate position. The second region is arranged in a predetermined position relative to the first region.

Abstract: An eye region is detected, in the detected eye region, the region of an iris outline is extended inward, and a hollow region surrounded by the extended region is detected as a poor hue quality region. An outline of the poor hue quality region is shaped by approximating the outline to one of a circle and an ellipse. The hue of the shaped poor hue quality region is corrected on the basis of color information obtained from a neighboring region inside an iris outline.

Abstract: A battery case is formed by drawing a metallic plate thin to form a cylindrical body 10 having a closed end and cutting away part of the cylindrical body 10 at an opening 11 thereof in the direction perpendicular to an axis of the cylindrical body 10. The cutting of the cylindrical body 10 is carried out by moving a second blade 30 arranged outside the cylindrical body 10 relatively toward the axis of the cylindrical body with a first blade kept abutting the inner circumference of the cylindrical body 10. As a result, an inward burr 13 extending in the direction perpendicular to the side face of the cylindrical body 10 is formed on a cut surface 12 of the cylindrical body 10, but the burr 13 is prevented from entering the battery case.

Abstract: In an image within which a face pattern is detected, when a ratio of a skin color pixel is equal to or smaller than a first threshold value in a first region and a ratio of a skin color pixel is equal to or greater than a second threshold value in a second r region, the vicinity of the first region is determined to be a face candidate position at which the face pattern can exist. Face detection is carried out on the face candidate position. The second region is arranged in a predetermined position relative to the first region.

Abstract: A line-of-sight detection apparatus includes a detection unit configured to detect a face from image data, a first extraction unit configured to extract a feature amount corresponding to a direction of the face from the image data, a calculation unit configured to calculate a line-of-sight reliability of each of a right eye and a left eye based on the face, a selection unit configured to select an eye according to the line-of-sight reliability, a second extraction unit configured to extract a feature amount of an eye region of the selected eye from the image data, and an estimation unit configured to estimate a line of sight of the face based on the feature amount corresponding to the face direction and the feature amount of the eye region.

Abstract: Pattern recognition capable of robust identification for the variance of an input pattern is performed with a low processing cost while the possibility of identification errors is decreased. In a pattern recognition apparatus which identifies the pattern of input data from a data input unit (11) by using a hierarchical feature extraction processor (12) which hierarchically extracts features, an extraction result distribution analyzer (13) analyzes a distribution of at least one feature extraction result obtained by a primary feature extraction processor (121). On the basis of the analytical result, a secondary feature extraction processor (122) performs predetermined secondary feature extraction.

Abstract: In an image capturing apparatus, a video input unit (2) captures the image of an object and sequentially acquires image data associated with the image capturing, a model data memory (6) stores model data associated with the first feature quantity calculated from a feature point of the object in a model image, a principal object detection unit (3) calculates the second feature quantity from a feature point of the object in the acquired image data, a state change estimation unit (4) estimates, on the basis of the second feature quantity and the model data, the timing when the object satisfies a predetermined condition, and an image input processing control unit (7) stores the image data corresponding to the estimated timing in an image recording unit (5). This configuration makes the image capturing apparatus acquire an image in a more proper state without large-capacity memory.

Abstract: A feature point detection unit (153) and feature amount extraction unit (154) extract a plurality of features of an object from input image data. When there are unextracted features of the plurality of features, a weight setting unit (155) sets weights for the extracted features. A facial expression determination unit (156) executes recognition processing of the object based on the features weighted by the weight setting unit (155).

Abstract: A feature point detection unit (153) and feature amount extraction unit (154) extract a plurality of features of an object from input image data. When there are unextracted features of the plurality of features, a weight setting unit (155) sets weights for the extracted features. A facial expression determination unit (156) executes recognition processing of the object based on the features weighted by the weight setting unit (155).

Abstract: The present invention facilitates the setting of a condition for the execution of predetermined processing and enables the execution of processing conforming to a user's intention. In an image processing apparatus, a predetermined object is detected in an image selected based on an instruction from a user, a determination is made regarding an attribute of the detected object, and the determined attribute is set as an execution condition used when executing predetermined processing on an image.

Abstract: An information processing apparatus that discriminates the orientation of a target includes a calculation unit that calculates a distribution of a difference in feature amount between a plurality of learning patterns each showing the orientation of a target, a determination unit that determines, using a probability distribution obtained from the distribution of differences calculated by the calculation unit, a pixel that is in an input pattern and is to be referred to in order to discriminate the orientation of a target in the input pattern, and a discrimination unit that performs discrimination for obtaining the orientation of the target in the input pattern by comparing a feature amount of the pixel determined by the determination unit and a threshold set in advance.

Abstract: An information processing apparatus comprises: a creation unit adapted to create a query string, which is composed of a plurality of queries; a reading unit adapted to read, from the query string, a query corresponding to a hierarchy of a current node in accordance with the hierarchy; a generation unit adapted to generate a plurality of nodes having a tree structure by dividing a learning pattern set in the current node in accordance with the read query corresponding to the hierarchy; and a modifying unit adapted to modify the tree structure by putting nodes in each hierarchy together into a common node with respect to nodes up to a hierarchy corresponding to a length of the query string among the nodes having the tree structure, which have been generated by the generation unit.

Abstract: An image processing apparatus stores model information representing a subject model belonging to a specific category, detects the subject from an input image by referring to the model information, determines a region for which an image correction is to be performed within a region occupied by the detected subject in the input image, stores, for a local region of the image, a plurality of correction data sets representing correspondence between a feature vector representing a feature before correction and a feature vector representing a feature after correction, selects at least one of the correction data sets to be used to correct a local region included in the region determined to undergo the image correction, and corrects the region determined to undergo the image correction using the selected correction data sets.

Abstract: A photoelectric conversion device manufacturing system in which a photoelectric conversion device is manufactured, the photoelectric conversion device including a p-type semiconductor layer, an i-type semiconductor layer, and an n-type semiconductor layer which are sequentially layered on a transparent-electroconductive film formed on a substrate in the photoelectric conversion device.