Abstract: An object detection apparatus first sets a first partial region having a preset size and a second partial region in a given point (pixel) in an input image. In addition, the object detection apparatus calculates a first information amount in the second partial region, and sets a third partial region based on the size of the first information amount. Furthermore, the object detection apparatus calculates a score based on a salience degree that is based on a difference in statistical feature amount distribution between the first partial region and the second partial region, and based on an information amount of feature amount in the third partial region. Lastly, the object detection apparatus detects a main object by calculating scores on the respective points in the image and applying a predetermined statistical process to the scores.

Abstract: An object detection apparatus first sets a first partial region having a preset size and a second partial region in a given point (pixel) in an input image. In addition, the object detection apparatus calculates a first information amount in the second partial region, and sets a third partial region based on the size of the first information amount. Furthermore, the object detection apparatus calculates a score based on a salience degree that is based on a difference in statistical feature amount distribution between the first partial region and the second partial region, and based on an information amount of feature amount in the third partial region. Lastly, the object detection apparatus detects a main object by calculating scores on the respective points in the image and applying a predetermined statistical process to the scores.

Abstract: There is provided with a convolution operation apparatus. A first product-sum calculator includes a plurality of first multipliers, a plurality of first accumulators, a first data supplier which supplies first data to the plurality of first multipliers, and a second data supplier which supplies a plurality of second data to the plurality of first multipliers. A second product-sum calculator includes a plurality of second multipliers, a plurality of second accumulators, a third data supplier which supplies third data to the plurality of second multipliers, and a fourth data supplier which receives and holds an output from each of the plurality of first accumulators and supply the outputs as fourth data to a corresponding one of the plurality of second multipliers.

Abstract: To enable a response to an urgent call-out caused by a failure occurrence, the degree of an occurrence of a failure in each of a plurality of apparatuses installed at different locations is predicted and a visit plan of each of a plurality of servicemen is created based on a prediction result.

Abstract: An image processing apparatus, an image processing method, and a recording medium realize identification of an object region and a region category with high precision, estimate a relationship between partial regions in an acquired image by using a database about relationships between the images, and determine a target region in the acquired image based on the relationship.

Abstract: 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.

Abstract: An information processing apparatus and method enables a pattern discriminator to learn. The apparatus establishes a branch structure appropriate for learning a discriminator having the branch structure without increasing processing time. The apparatus includes a preliminary learning unit to learn a preliminary discriminator for a respective one of a plurality of combinations of variations in variation categories in a discrimination target pattern. A branch structure determination unit is provided to perform discrimination processing using the preliminary discriminator and to determine a branch structure of a main discriminator based on a result of the discrimination processing. A main learning unit is included to learn the main discriminator based on the branch structure.

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: The accuracy of estimating the category of an object in an image and its region is improved. The present invention detects as to whether each of a plural types of objects is included in an object image, forms a plurality of local regions in a region including the object detected, and calculates a feature quantity of the plurality of local regions formed. Furthermore, the present invention selects a discriminant criterion adapted to the type of the object detected, from a plurality of discriminant criteria for discriminating the plural types of objects, and determines, based on the discriminant criterion selected and the feature quantity calculated, a region of the object detected from the plurality of local regions.

Abstract: A probability at which a target object takes a target object state is acquired for each of target object states that the target object is allowed to take, and a distribution of the probabilities is acquired. A success rate is acquired, for each relative target object state being determined in advance for a position and orientation of an image capturing device, at which the target object is successfully identified from a captured image obtained by capturing the target object having the relative target object state, and a distribution of the success rates is acquired. A position and orientation that the device is to take is determined based on the distribution of the success rates acquired for each of a plurality of positions and orientations that the image capturing apparatus is allowed to take, and the distribution of the probabilities.

Abstract: An object detection apparatus first sets a first partial region having a preset size and a second partial region in a given point (pixel) in an input image. In addition, the object detection apparatus calculates a first information amount in the second partial region, and sets a third partial region based on the size of the first information amount. Furthermore, the object detection apparatus calculates a score based on a salience degree that is based on a difference in statistical feature amount distribution between the first partial region and the second partial region, and based on an information amount of feature amount in the third partial region. Lastly, the object detection apparatus detects a main object by calculating scores on the respective points in the image and applying a predetermined statistical process to the scores.

Abstract: A recognition apparatus according to an embodiment of the present invention includes: a candidate region extraction unit configured to extract a subject candidate region from an image; a feature value extraction unit configured to extract a feature value related to an attribute of the image from the subject candidate region extracted by the candidate region extraction unit; an attribute determination unit configured to determine an attribute of the subject candidate region extracted by the candidate region extraction unit on the basis of the feature value extracted by the feature value extraction unit; and a determination result integration unit configured to identify an attribute of the image by integrating determination results of the attribute determination unit.

Abstract: The robustness of discriminating results at each stage is improved in discrimination processing in which a plurality of stages of discriminators are used to identify an object. An information processing apparatus in which a plurality of stages of the discriminators are used to identify a class of an object, comprises a candidate class output unit that acquires as a candidate class a class discriminated at a first stage of the discriminators, and an extended class setting unit that sets in a second stage of the discriminators, a class of a second stage of the discriminators, which is defined as an extended partial space of a partial space defined by a candidate class in a discriminating space used in discriminating the candidate class by the first stage of the discriminators, as a class to be discriminated at this second stage of the discriminators.

Abstract: Even when a local area is varied, degradation in recognition accuracy and detection accuracy is suppressed. To that end, a pattern processing apparatus includes a reference local area setting portion 1802 for setting a reference local area based on the detection result of a feature point by a face organ feature point detecting portion 101, a varied local area generating portion 1803 for generating a plurality of varied local area patterns by referring to an image area near the reference local area, a similarity calculating portion 106 for calculating similarities in the reference local areas and in the varied local area patterns between the input pattern and the registered pattern, a representative similarity calculating portion 107 for calculating representative similarity from among the similarities, and a classifying portion 109 for determining a class to which the input pattern belongs.

Abstract: A pattern recognition apparatus that recognizes a data attribute of input data calculates correlation values of feature quantities of corresponding local patterns between the input data and dictionary data for each of a plurality of dictionary data prepared for each data attribute, combines, for each data attribute, the calculated correlation values of local patterns of each dictionary datum to acquire a set of correlation values of each data attribute, integrates correlation values included in each set of correlation values of each data attribute to calculate a similarity of the input data for each data attribute, and identifies the data attribute of the input data based on the calculated similarity.

Abstract: Corresponding partial features are extracted from an input pattern and a registration pattern as a preregistered pattern. A plurality of combinations of the partial features are generated as composited partial features. One of registration pattern classes to which the input pattern corresponds is identified by using the plurality of composited partial features. The identification is performed based on the result of evaluation of the partial features which belong to the composited partial feature and correspond to each other in the input pattern and the registration pattern. In the evaluation, the composited partial feature is evaluated based on the measurement result of the quantity of partial features meeting a predetermined criterion.

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 sets a plurality of reference locations of data in information as one reference location pattern and acquires a feature amount obtained from a value of data of one of the plurality of pieces of reference information in one reference location pattern for each of a plurality of reference location patterns and the plurality of pieces of reference information. The apparatus extracts data included in the input information according to each of the plurality of reference location patterns, selects the reference location pattern for classification of the input information from the plurality of reference location patterns based on a value of data included in the extracted input information, and executes classification of the input information by using the feature amount in the selected reference location pattern and data included in the input information at a reference location indicated by the reference location pattern.

Abstract: An image including a face is input (S201), a plurality of local features are detected from the input image, a region of a face in the image is specified using the plurality of detected local features (S202), and an expression of the face is determined on the basis of differences between the detection results of the local features in the region of the face and detection results which are calculated in advance as references for respective local features in the region of the face (S204).

Abstract: A network camera system is provided that detects an occurrence of a condition change at a periphery of an image pickup apparatus, obtains a direction of the detected condition change, and notifies a user of the occurrence of the condition change and a direction of the condition change on a display of a terminal device.