Abstract: According to the present disclosure, a weight parameter of a neural network is divided into a plurality of portions having a certain size and approximation is individually performed on the portions using a weighted sum of the codebook vectors.

Abstract: The present invention aims to estimate a more consistent posture in regard to a multi-joint object. A target range image is first input, a human body region is extracted from the input range image, a target joint position candidate is calculated from the input range image, and a joint position is finally determined based on the calculated joint position candidate and a likelihood of each joint to estimate the posture. At this time, joint position permissible range information concerning inter-joint distance and angle of a human body model previously set by learning is obtained from a human body model storing unit, consistency is evaluated for a relation between the joint position candidates of a certain joint and other joint based on the obtained information, and thus the posture corresponding to the best combination of the joint positions is determined.

Abstract: An image recognition apparatus is provided which comprises a first extracting means for extracting, from every registration image previously registered, a set of registration partial images of a predetermined size, and a second extracting means for extracting, from an input new image, a set of new partial images of a predetermined size. The apparatus further comprises a discriminating means for discriminating an attribute of the new partial image based on a rule formed by dividing the set of the registration partial images extracted by the first extracting means, and a collecting means for deriving a final recognition result of the new image by collecting discrimination results by the discriminating means at the time when the new partial images as elements of the set of the new partial images are input.

Abstract: A data processing method includes setting a learning data set including a plurality of learning data having respective labels to an uppermost node of a decision tree, setting selection probabilities of the learning data, selecting a combination of the learning data from each of a plurality of sets of learning data assigned to nodes of the decision tree in accordance with the selection probabilities, determining a branch rule for dividing each of the sets of the learning data assigned to the nodes of the decision tree into at least two subsets using the selected combination of the learning data, and assigning the subsets divided in accordance with the branch rule to nodes in a lower level.

Abstract: An event detection apparatus includes an input unit configured to input a plurality of time-sequential images, a first extraction unit configured to extract sets of first image samples according to respective different sample scales from a first time range of the plurality of time-sequential images based on a first scale parameter, a second extraction unit configured to extract sets of second image samples according to respective different sample scales from a second time range of the plurality of time-sequential images based on a second scale parameter, a dissimilarity calculation unit configured to calculate a dissimilarity between the first and second image samples based on the sets of the first and second image samples, and a detection unit configured to detect an event from the plurality of time-sequential images based on the dissimilarity.

Abstract: The present invention aims to estimate a more consistent posture in regard to a multi-joint object. A target range image is first input, a human body region is extracted from the input range image, a target joint position candidate is calculated from the input range image, and a joint position is finally determined based on the calculated joint position candidate and a likelihood of each joint to estimate the posture. At this time, joint position permissible range information concerning inter-joint distance and angle of a human body model previously set by learning is obtained from a human body model storing unit, consistency is evaluated for a relation between the joint position candidates of a certain joint and other joint based on the obtained information, and thus the posture corresponding to the best combination of the joint positions is determined.

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: An information processing apparatus comprises: a registration unit adapted to register information required to determine at least one specific pattern in an image; an input unit adapted to input image data; a first generation unit adapted to extract a predetermined feature distribution from the input image data, and to generate a first feature distribution map indicating the feature distribution; a second generation unit adapted to generate a second feature distribution map by applying a conversion required to relax localities of the first feature distribution map to the first feature distribution map; and a determination unit adapted to determine, using sampling data on the second feature distribution map and the registered information, which of the specific patterns the image data matches.

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 information processing apparatus includes an irradiation unit to irradiate a measurement target with a measurement pattern for distance measurement. An imaging unit obtains a captured image including the irradiated measurement target. A first detection unit detects first and second regions from the captured image. The first region includes a first portion of the measurement target that reflects a greater amount of light toward the imaging unit. The second region includes a second portion of the measurement target that reflects a lesser amount of light toward the imaging unit. A second detection unit detects, from the measurement pattern, a first region with which the first portion is irradiated and a second region with which the second portion is irradiated. A generation unit generates a measurement pattern that has different amounts of irradiation light depending on regions. A distance to the measurement target is derived using an obtained captured image.

Abstract: A recognition training apparatus according to the present invention includes a generation unit configured to generate relevance between a specific domain and a candidate of a recognition target based on ontology information expressing a concept structure of the specific domain, a selection unit configured to select the recognition target from the candidate of the recognition target based on the relevance generated by the generation unit, and a training unit configured to train a recognizer using training data regarding the recognition target selected by the selection unit.

Abstract: An image processing system comprises: an image recognizing unit which performs image recognition to an image; a rule setting unit which sets a sorting rule to be used in case of transmitting the image recognized by the image recognizing unit to an external web service; and a transmitting unit which transmits, according to the sorting rule having a condition conforming to the image among the sorting rules set by the rule setting unit, information concerning the image to the corresponding external web service, thereby enabling to cooperate a still image/moving image sharing service and various web services with others.

Abstract: A feature selection apparatus, which selects features to be used to discriminate an object by a discriminator using learning data including the object, extracts a plurality of partial data from the learning data, and obtains discrimination values obtained by controlling the discriminator to process the plurality of extracted partial data as features of the plurality of partial data. The feature selection apparatus evaluates the obtained features based on discrimination degrees on a discrimination space defined by the discriminator, and selects features to be used to discriminate the object from a plurality of features obtained in association with the plurality of partial data based on an evaluation result.

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 resource allocation apparatus. An attribute indicating a requirement for a data storage resource to be allocated to a plurality of data flows to which the attribute is provided beforehand is acquired. A data flow relationship graph indicating a relationship between the plurality of data flows which potentially lead to access contention in the data storage resource is generated. Based on the attribute and the data flow relationship graph, allocation of the data storage resource to the plurality of data flows is determined such that no access contention occurs.

Abstract: An image processing apparatus includes an acquisition unit, a first detection unit, a selection unit, and a correction unit. The acquisition unit acquires an image including a target object having a plurality of parts. The first detection unit detects a candidate region of each of the plurality of parts of the target object included in the acquired image using a previously learned model. The selection unit selects, based on the candidate region detected by the first detection unit, a first part having relatively high reliability and a second part having relatively low reliability from among the plurality of parts. The correction unit corrects the model by changing a position of the second part based on the first part selected by the selection unit.

Abstract: An image processing apparatus includes an extraction unit, a setting unit, a reference value calculation unit, a comparison unit, and an information determination unit. The extraction unit extracts a target area from an image. The setting unit sets a pixel from the target area as a pixel-of-interest. The reference value calculation unit calculates a reference value based on a pixel value of at least one or more pixels included in the target area. The comparison unit repeatedly performs processing of comparing a pixel value of at least one or more pixels among a plurality of pixels in a predetermined layout with respect to the pixel-of-interest with the reference value. The information determination unit determines information of the pixel-of-interest based on a comparison result of the comparison unit and a value corresponding to the comparison result.

Abstract: An information processing apparatus includes an imaging unit and is capable of setting arrangement of a structural member of a robot system which works based on an image captured by the imaging unit. The information processing apparatus includes an arrangement unit configured to arrange a virtual object corresponding to the structural member in a virtual space corresponding to a working space of the robot system, a first acquisition unit configured to acquire a virtual space image in the virtual space which corresponds to the captured image and in which the virtual object is arranged, and a second acquisition unit configured to acquire an evaluation value indicating adaptation of arrangement of the virtual object to the work of the robot system based on the virtual space image.

Abstract: In a mirror system for displaying an image on a mirror surface, a mirror reflects incident light from an object facing its front surface side to present a reflected image, and transmits incident light from its rear surface. A display unit generates a presentation image to be superimposed on the reflected image. An optical unit is arranged between the display unit and the rear surface of the mirror, and images the presentation image. An acquisition unit acquires distance information between the object and the mirror. A controller controls the imaging point of the presentation image by the optical unit according to the distance information.

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.