Canon Kabushiki Kaisha

Takahisa Yamamoto

Yoshinori Ito

Masami Kato

Katsuhiko Mori

Keiichi Iwamura

Takashi Suzuki

Osamu Nomura

Atsuo Nomoto

Hideo Noro

Masao Yamanaka

Shunsuke Nakano

Yuji Kaneda

Satoshi Yashiro

Kiyotaka Takahashi

Masakazu Matsugu

Kotaro Yano

Toru Nakata

Koji Makita

Hiroshi Sato

Kan Torii

Akira Ohno

Tomoya Honjo

Masayoshi Yamasaki

Daisuke Nishino

Yusuke Yachide

There is provided with an information processing apparatus. An extracting unit extracts a feature vector of a subject in an image. A generating unit configured to generate, based on the feature vector, a post-conversion vector including a converted vector resulting from conversion of the feature vector using a random number, the post-conversion vector being a vector whose number of elements is determined according to the random number and is larger than a number of elements of the feature vector.

Information identification processing apparatus, information identification processing method, image identification system, and storage medium

An image processing apparatus includes a first extraction unit configured to subject an input image to first extraction processing to extract a first feature quantity, a second extraction unit configured to subject the input image to second extraction processing having a lower throughput than the first extraction processing to extract a second feature quantity, a comparison unit configured to compare the first feature quantity with the second feature quantity and then output a comparison result, and an update unit configured to update parameters to be used for the second extraction processing by the second extraction unit, based on the comparison result.

Image processing apparatus, image processing method, image input apparatus, image processing system, and program

There is provided with an image identification apparatus. An extraction unit extracts a feature value of an image from image data using a Neural Network (NN). A processing unit identifies the image based on the feature value extracted by the extraction unit. The NN comprises a plurality of calculation layers connected hierarchically. The NN includes a plurality of sub-neural networks for performing processing of calculation layers after a specific calculation layer. Mutually different data from an output of the specific calculation layer are respectively inputted to the plurality of sub-neural networks.

Image identification apparatus, image identification method, training apparatus, and neural network having sub-neural networks respectively inputted with mutually different data

To allow arithmetic processing using a plurality of processing nodes to be executed with a smaller memory size, an arithmetic processing apparatus for executing processing using a hierarchical type network formed by the plurality of processing nodes, comprises: a storage unit configured to store a parameter used by each of the plurality of processing nodes for arithmetic processing and a calculation result of the arithmetic processing in each of the plurality of processing nodes; and a buffer control unit configured to switch, based on a configuration of the hierarchical type network, a buffer system of the parameter and the calculation result in the storage unit in at least one layer of the hierarchical type network.

Arithmetic processing apparatus and control method therefor

An information processing apparatus includes detecting a predetermined object from a captured image, identifying an attribute of the detected object, determining a presentation method of presented information representing the attribute based on a detection state of the detected object, displaying the presented information and the captured image based on the determined presentation method.

Information processing apparatus, image display method, and non-transitory computer-readable storage medium for display control

A data processing apparatus includes a storage unit configured to store reference data of a filter operation and coefficient data of filters, a plurality of operators configured to parallelly perform the filter operation on the reference data and the coefficient data of the filters, a first supply unit configured to supply reference data transferred from the storage unit to the plurality of operators, a second supply unit configured to supply coefficient data of a first and second filters transferred from the storage unit to the plurality of operators, and a control unit configured to control the second supply unit to supply the coefficient data of the first filter to a first operator, and supply the coefficient data of the second filter to a second operator.

Convolutional neural network based data processing apparatus, method for controlling the same, and storage medium storing program

An information processing apparatus includes an extraction unit that extracts a feature from an image including a face, a first estimation unit that estimates a likelihood of the face with respect to each generation based on the feature, a storage unit that stores a plurality of samples, the plurality of samples each including a generation-specific combination of likelihoods and a correct age as a pair, a selection unit that selects a sample from the storage unit based on a combination of likelihoods estimated by the first estimation unit, and a second estimation unit that estimates an estimated age of the face and an error range thereof based on the sample selected by the selection unit.

Information processing apparatus for estimating age and method thereof

By a first grouping pattern, a plurality of regions for which a filter operation is to be performed in an operation target image are grouped. Then, for each group obtained by the first grouping pattern, a first filter corresponding to the group is used to perform a filter operation on each region belonging to the group. By a second grouping pattern, a plurality of regions for which a filter operation is to be performed in an intermediate image obtained by the filter operation are grouped. Then, for each group obtained by the second grouping pattern, a second filter corresponding to the group is used to perform a filter operation on each region belonging to the group.

Image processing apparatus that performs filter operation on group of regions in an image, image processing method and non-transitory computer- readable storage medium

Information processing apparatus includes an input unit configured to input a captured image capturing a target object in a real environment, an obtaining unit configured to obtain an illumination condition in the real environment; a generation unit configured to generate a variation image as an image of a registration object reflecting the illumination condition based on three-dimensional data of the registration object and the obtained illumination condition, and a collation unit configured to collate the registration object with the target object based on a feature amount of the variation image and a feature amount of the captured image.

Apparatus for authenticating an object and method thereof

A region-of-interest detection apparatus for improving detection accuracy of a region of interest in a case where a region of interest overlaps a background region, or in a case where feature amounts of a region of interest and a background region are similar to each other calculates feature amounts of regions where partial regions and a background region set in an input image overlap each other, and based on the calculated feature amounts and a feature amount of each position in the input image, calculates a foreground level of the position in the input image. Then, the region-of-interest detection apparatus detects a region of interest from the input image based on the calculated foreground level and a saliency of the position.

Region-of-interest detection apparatus, region-of-interest detection method, and recording medium

An identification apparatus includes an acquisition unit configured to acquire input data and an identification unit configured to identify a class to which the acquired input data belongs based on a classifier configured to identify a class to which the data belongs from among a plurality of classes that includes two or more classes having been set beforehand.

Image identification apparatus and image identification method

A degree-of-saliency map generated from an input image is divided into a plurality of partial areas, and the degree of nonuniformity is calculated from the distribution characteristics of the degrees of saliency of the partial areas. Whether a main subject is present in the input image is judged based on the calculated degree of nonuniformity.

Main-subject detection method, main-subject detection apparatus, and non-transitory computer readable storage medium

An image processing apparatus includes an imaging unit, a determination unit, and a discrimination unit. The imaging unit images a target object using signals in a predetermined wavelength band in which a spectral transmittance of a specific substance of a plurality of substances on a surface of the target object is different from a spectral transmittance of the other substances of the plurality of substances. The determination unit determines a distribution state of the specific substance on the surface of the target object based on an image captured by the imaging unit. The discrimination unit discriminates a class to which the target object belongs based on the distribution state of the specific substance.

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Kawasaki, Japan

Takahisa Yamamoto