Canon Kabushiki Kaisha

Kan Torii

Masakazu Matsugu

Takashi Inoue

Katsuhiko Mori

Takashi Suzuki

Yusuke Mitarai

Mamoru Osada

Tomoko Takagi

Naoko Shimotai

Yasuhiko Sasaki

Tomoaki Endoh

Kenji Tsukamoto

Masami Kato

Yasuhiro Sasaki

Yuji Kaneda

Atsushi Nogami

Tomoaki Endo

Yoshinori Ito

Takahisa Yamamoto

Yasuo Katano

Kaname Tomite

Hiromi Shiozaki

Takayuki Iwamoto

An object detection method includes an image acquisition step of acquiring an image including a target object, a layer image generation step of generating a plurality of layer images by one or both of enlarging and reducing the image at a plurality of different scales, a first detection step of detecting a region of at least a part of the target object as a first detected region from each of the layer images, a selection step of selecting at least one of the layer images based on the detected first detected region and learning data learned in advance, a second detection step of detecting a region of at least a part of the target object in the selected layer image as a second detected region, and an integration step of integrating a detection result detected in the first detection step and a detection result detected in the second detection step.

Object detection method, object detection apparatus, and program

An object detection apparatus includes a first detection unit configured to detect a first portion of an object from an input image, a second detection unit configured to detect a second portion different from the first portion of the object, a first estimation unit configured to estimate a third portion of the object based on the first portion, a second estimation unit configured to estimate a third portion of the object based on the second portion, a determination unit configured to determine whether the third portions, which have been respectively estimated by the first and second estimation units, match each other, and an output unit configured to output, if the third portions match each other, a detection result of the object based on at least one of a detection result of the first or second detection unit and an estimation result of the first or second estimation unit.

Object detection apparatus and method therefor

A learning apparatus comprises a plurality of detection units configured to detect a part or whole of a target object in an image and output a plurality of detection results; an estimation unit configured to estimate a state of the target object based on at least one of the plurality of detection results; a classification unit configured to classify the image into a plurality of groups based on the state of the target object; and a weight calculation unit configured to calculate weight information on each of the plurality of detection units for each of the groups based on the detection results.

Learning apparatus, method for controlling learning apparatus, detection apparatus, method for controlling detection apparatus and storage medium

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.

Method and apparatus for detecting and processing specific pattern from image

An information processing method comprises the steps of: inputting an input information of a multi-dimensional array; calculating an accumulated information value corresponding to a position of each element of the input information; and holding the accumulated information value in a buffer having a size of predetermined bits, wherein in the holding step, when an accumulated information value calculated in the calculating step overflows with respect to the size, a part not more than the predetermined bits of the calculated accumulated information value is held as the accumulated information value.

Information processing method and apparatus, program, and storage medium

A pattern recognition method, applicable to input information including a plurality of regions, includes obtaining a certainty at which each region of the input information includes a pattern, selecting one or more regions having a relatively high-level certainty among the plurality of regions, and performing pattern detection processing on the selected region or regions.

Method, apparatus, and computer-readable storage medium for pattern recognition

In a pattern identification method in which input data is classified into predetermined classes by sequentially executing a combination of a plurality of classification processes, at least one of the classification processes includes a mapping step of mapping the input data in an N (N&#x2267;2) dimensional feature space as corresponding points, a determination step of determining whether or not to execute the next classification process based on the corresponding points, and selecting step of selecting a classification process to be executed next based on the corresponding points when it is determined in the determination step that the next classification process should be executed.

Pattern identification method, parameter learning method and apparatus

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.

Learning apparatus for pattern detector, learning method and computer-readable storage medium

A method includes detecting a feature of an input pattern using a plurality of feature detectors, selecting at least one of the feature detectors based on their output values, and calculating a feature quantity of the input pattern based on an output value from at least one selected feature detector.

Method and apparatus for detecting a feature of an input pattern using a plurality of feature detectors, each of which corresponds to a respective specific variation type and outputs a higher value when variation received by the input pattern roughly matches the respective specific variation type

A plurality of pieces of learning data, each associated with a class to which the piece of the learning data belong, are input. In each piece of the learning data, a statistical amount of attribute values of elements in each of specific k parts, k being equal to or larger than 1, is calculated. Each piece of the learning data is mapped in a k-dimensional feature space as a vector having the calculated k statistics amounts as elements. Based on each piece of the mapped learning data and the classes to which the pieces of learning data belong, parameters for classifying input data into one of the plurality of classes are learned in the k-dimensional feature space. By using the parameters, pattern classification can be performed with high speed and high accuracy.

Parameter learning method, parameter learning apparatus, pattern classification method, and pattern classification apparatus

There is disclosed an information processing apparatus which is handy for a user. In the information processing apparatus, a user interface of a control program for controlling a peripheral is automatically formed in accordance with a function obtained from the peripheral.

Information processing apparatus, information processing method, information processing system, and storage medium for storing information processing program

The present invention provides an information processing apparatus in which a limiting value of a counter for restricting the use of the apparatus can be dynamically set and changed in a secure method and a controlling method of the information processing apparatus. License information including an appliance serial number of a copy machine SCand a new limiting value is input to the copy machine with a counter function that restricts a function when a counter value reaches a limiting value. The input license information is determined whether it is valid or not. If it is determined valid, a saved limiting value is updated to the new limiting value included in the license information.

Information processing apparatus and controlling method of the same

An authentication apparatus for solving problems involving convenience and security is disclosed. The authentication apparatus according to the present invention is an authentication apparatus having a plurality of authentication mechanisms, the apparatus determining (S) whether authentication information that has been input by a card reader for inputting authentication information of an object of authentication is that of a user who is capable of changing over the plurality of authentication mechanisms, displaying (S) a list of the plurality of authentication mechanisms if it is determined that the user is capable of making the changeover, and registering (S) the authentication mechanism, which has been selected in the display list, as the effective authentication mechanism.

Growing community of inventors

Tokyo, Japan

Kan Torii