摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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).
摘要:
A battery can of the present invention ensures a stable and favorable contact with an electrode and thus makes it possible to obtain a highly reliable battery excellent in high rate discharge characteristics. The battery can having an opening, including a cylindrical side portion and a bottom portion, of the present invention is formed from a steel plate. The steel plate has an Ni—Fe alloy layer on the inner face side of the battery can. The Ni—Fe alloy layer has an oxide layer containing iron and having a thickness of 10 to 50 nm on the inner face side of the battery can.
摘要:
At least one exemplary embodiment is directed to an imaging processing method where a plurality of images are picked up while an imaging direction of a camera is being changed. The images are combined into a composite image. A target region is specified within the composite image. An imaging direction and an imaging magnification for imaging an object included in the target region in a predetermined size are calculated based on a position and a size of the target region in the composite image and an imaging parameter set for the camera when the plurality of images are picked up. Accordingly, the imaging direction and the imaging magnification for imaging the object to be imaged can be set easily.
摘要:
A pattern recognition apparatus that is lightweight for mounting, and reduces the effects of registration conditions or check conditions on recognition accuracy. Similarity sets for respective local features are calculated from a local feature of input data and local features of a plurality of pieces of dictionary data corresponding to the local feature of the input data. Integrated similarities are calculated by integrating a plurality of similarity sets in the local features according to a registration condition or a check condition. Dictionary data corresponding to the input data is identified based on the calculated integrated similarities.
摘要:
In a hierarchical neural network having a module structure, learning necessary for detection of a new feature class is executed by a processing module which has not finished learning yet and includes a plurality of neurons which should learn an unlearned feature class and have an undetermined receptor field structure by presenting a predetermined pattern to a data input layer. Thus, a feature class necessary for subject recognition can be learned automatically and efficiently.