Patents by Inventor Susumu Kubota

Susumu Kubota has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20180239458
    Abstract: According to an embodiment, a device includes a memory and processing circuitry. When time taken by a user to carry out first behavior is equal to or more than a first threshold, or when number of times the first behavior is repeated is equal to or more than a second threshold, the processing circuitry is configured to output first guidance to lead the user to first expected behavior that is behavior the user is expected to carry out subsequent to the first behavior. When the time taken to carry out the first behavior is less than the first threshold, or when the number of times the first behavior is repeated is less than the second threshold, the processing circuitry is configured to omit the first guidance to lead the user to the first expected behavior or outputs second guidance that is simpler than the first guidance.
    Type: Application
    Filed: August 7, 2017
    Publication date: August 23, 2018
    Applicant: Kabushiki Kaisha Toshiba
    Inventors: Yuta SHIRAKAWA, Tatsuo KOZAKAYA, Susumu KUBOTA, Satoshi ITO, Quoc Viet PHAM
  • Patent number: 9830363
    Abstract: According to an embodiment, an apparatus includes a calculator, an pixel evaluator, an accumulator, and an area evaluator. The calculator is configured to calculate a feature of an image for each pixel in image data. The pixel evaluator is configured to produce a score that evaluates the feature for each pixel. The accumulator is configured to calculate, for each pixel, a cumulative score obtained by accumulating all scores in an area including a minor angle formed by a half line in a first direction from the each pixel position and another half line in a second direction from the each pixel position. The area evaluator is configured to calculate an evaluation value that is a total of the scores in a quadrilateral area enclosed by two lines of the first direction and two lines of the second direction based on the cumulative scores at pixel positions at vertexes of the quadrilateral area.
    Type: Grant
    Filed: February 9, 2016
    Date of Patent: November 28, 2017
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Tomoki Watanabe, Susumu Kubota, Satoshi Ito, Tomohiro Nakai
  • Patent number: 9779062
    Abstract: According to an embodiment, a computing apparatus includes a memory, and a processor. The memory stores N first vectors in a d-dimensional binary vector space consisting of binary values. The processor acquires a second vector in the d-dimensional binary vector space. The processor extracts M first vectors having a distance from the second vector satisfying a first condition out of the N first vectors, and calculate a distribution of distances of the M first vectors from the second vector. The processor acquires a first kernel function per a first distance between the M first vectors and the second vector in a first range. The processor generates a second kernel function based on the distribution and the first kernel functions. The processor calculates an occurrence probability of the second vector in the N first vectors based on the second kernel function.
    Type: Grant
    Filed: November 10, 2015
    Date of Patent: October 3, 2017
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Satoshi Ito, Susumu Kubota, Tomohiro Nakai
  • Patent number: 9639779
    Abstract: According to an embodiment, a feature point detection device includes a generator to generate a K-class classifier and perform, for T times, an operation in which a first displacement vector is obtained that approximates D number of initial feature points of each training sample classified on a class-by-class basis to true feature points; a calculator to calculate, from the first displacement vectors, second displacement label vectors each unique to one second displacement vector, and a second displacement coordinate vector common to the second displacement vectors; a classifier to apply the K-class classifiers to the input image and obtain a second displacement label vector associated with a class identifier output from each K-class classifier; an adder to add up the second displacement label vectors; and a detector to detect D number of true feature points based on the initial feature points, the added label vector, and the second displacement coordinate vector.
    Type: Grant
    Filed: September 9, 2015
    Date of Patent: May 2, 2017
    Assignee: KABUSHIKI KAISHA TOSHIBA
    Inventors: Tatsuo Kozakaya, Tomokazu Kawahara, Susumu Kubota
  • Publication number: 20170091581
    Abstract: According to an embodiment, a computing device includes a processing circuitry. The processing circuitry receives an input of tensor data. The processing circuitry sets a window in the tensor data. The processing circuitry compares, for each pair of coordinates in the tensor data within the window, a pixel value at the pair of coordinates with one or more thresholds, and selects a weight value corresponding to a comparison result. The processing circuitry adds the weight values selected for the respective pairs of coordinates to obtain a cumulative value. The processing circuitry derives a value based at least in part on the cumulative value.
    Type: Application
    Filed: September 6, 2016
    Publication date: March 30, 2017
    Inventors: Tomoki WATANABE, Satoshi ITO, Susumu KUBOTA
  • Publication number: 20160239984
    Abstract: According to an embodiment, an apparatus includes a calculator, an pixel evaluator, an accumulator, and an area evaluator. The calculator is configured to calculate a feature of an image for each pixel in image data. The pixel evaluator is configured to produce a score that evaluates the feature for each pixel. The accumulator is configured to calculate, for each pixel, a cumulative score obtained by accumulating all scores in an area including a minor angle formed by a half line in a first direction from the each pixel position and another half line in a second direction from the each pixel position. The area evaluator is configured to calculate an evaluation value that is a total of the scores in a quadrilateral area enclosed by two lines of the first direction and two lines of the second direction based on the cumulative scores at pixel positions at vertexes of the quadrilateral area.
    Type: Application
    Filed: February 9, 2016
    Publication date: August 18, 2016
    Inventors: Tomoki WATANABE, Susumu KUBOTA, Satoshi ITO, Tomohiro NAKAI
  • Patent number: 9390347
    Abstract: A recognition device includes a storage unit, an acquiring unit, a first calculator, a second calculator, a determining unit, and an output unit. The storage unit stores multiple training patterns each belonging to any one of multiple categories. The acquiring unit acquires a recognition target pattern to be recognized. The first calculator calculates, for each of the categories, a distance histogram representing distribution of the number of training patterns belonging to the category with respect to distances between the recognition target pattern and the training patterns belonging to the category. The second calculator analyzes the distance histogram of each of the categories to calculate confidence of the category. The determining unit determines a category of the recognition target pattern from the multiple categories by using the confidences. The output unit outputs the category of the recognition target pattern.
    Type: Grant
    Filed: December 18, 2013
    Date of Patent: July 12, 2016
    Assignee: KABUSHIKI KAISHA TOSHIBA
    Inventors: Tomohiro Nakai, Susumu Kubota, Satoshi Ito
  • Publication number: 20160133008
    Abstract: According to one embodiment, a crack data collection method includes acquiring an image obtained by photographing an inspection object region for a crack in a structure, detecting a crack pixel group included in the inspection object region from the image, successively setting turning points from a starting point to an end point on a contour of the crack pixel group, and analyzing and collecting positions of the starting point, the turning points, and the end point and a vector of each of the points, as crack data.
    Type: Application
    Filed: September 10, 2015
    Publication date: May 12, 2016
    Inventors: Takaaki Kuratate, Susumu Kubota, Norihiro Nakamura, Ryo Nakashima, Masaki Yamazaki, Akihito Seki
  • Publication number: 20160133007
    Abstract: According to one embodiment, a crack data collection apparatus includes an acquisition unit, a detector, a calculator and a storage unit. The acquisition unit acquires an image obtained by photographing an inspection object region for a crack in a structure. The detector detects a crack pixel group included in the inspection object region from the image. The calculator successively sets turning points from a starting point to an end point on a contour of the crack pixel group, and calculates positions of the starting point, the turning points, and the end point and a vector of each of the points as crack data, The storage unit stores the crack data.
    Type: Application
    Filed: September 10, 2015
    Publication date: May 12, 2016
    Inventors: Takaaki Kuratate, Susumu Kubota, Norihiro Nakamura, Ryo Nakashima, Masaki Yamazaki, Akihito Seki
  • Publication number: 20160132463
    Abstract: According to an embodiment, a computing apparatus includes a memory, and a processor. The memory stores N first vectors in a d-dimensional binary vector space consisting of binary values. The processor acquires a second vector in the d-dimensional binary vector space. The processor extracts M first vectors having a distance from the second vector satisfying a first condition out of the N first vectors, and calculate a distribution of distances of the M first vectors from the second vector. The processor acquires a first kernel function per a first distance between the M first vectors and the second vector in a first range. The processor generates a second kernel function based on the distribution and the first kernel functions. The processor calculates an occurrence probability of the second vector in the N first vectors based on the second kernel function.
    Type: Application
    Filed: November 10, 2015
    Publication date: May 12, 2016
    Inventors: Satoshi ITO, Susumu KUBOTA, Tomohiro NAKAI
  • Publication number: 20160086057
    Abstract: According to an embodiment, a feature point detection device includes a generator to generate a K-class classifier and perform, for T times, an operation in which a first displacement vector is obtained that approximates D number of initial feature points of each training sample classified on a class-by-class basis to true feature points; a calculator to calculate, from the first displacement vectors, second displacement label vectors each unique to one second displacement vector, and a second displacement coordinate vector common to the second displacement vectors; a classifier to apply the K-class classifiers to the input image and obtain a second displacement label vector associated with a class identifier output from each K-class classifier; an adder to add up the second displacement label vectors; and a detector to detect D number of true feature points based on the initial feature points, the added label vector, and the second displacement coordinate vector.
    Type: Application
    Filed: September 9, 2015
    Publication date: March 24, 2016
    Inventors: Tatsuo Kozakaya, Tomokazu Kawahara, Susumu Kubota
  • Patent number: 9237269
    Abstract: According to an embodiment, an image processing device includes a generator and a processor. The generator is configured to generate, from a plurality of unit images in which points on an object are imaged by an imaging unit at different positions according to distances between the imaging unit and the positions of the points on the object, a refocused image focused at a predetermined distance. The processor is configured to perform blurring processing on each pixel of the refocused image according to an intensity corresponding to a focusing degree of the pixel of the refocused image.
    Type: Grant
    Filed: July 9, 2013
    Date of Patent: January 12, 2016
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Toshiyuki Ono, Yasunori Taguchi, Takuma Yamamoto, Susumu Kubota, Nobuyuki Matsumoto
  • Publication number: 20150363667
    Abstract: According to an embodiment, a recognition device includes a memory to store therein learning patterns each belonging to one of categories; an obtaining unit to obtain a recognition target pattern; a first calculating unit to calculate, for each category, a distance histogram representing distribution of the number of learning patterns belonging to the categories with respect to distances between the recognition target pattern and the learning patterns belonging to the categories; a second calculating unit to analyze the distance histogram of each category, and calculate a feature value of the recognition target pattern; a third calculating unit to make use of the feature value and one or more classifiers, and calculate degrees of reliability of the recognition target categories; and a determining unit to make use of the degrees of reliability and, from among the one or more recognition target categories, determine a category of the recognition target pattern.
    Type: Application
    Filed: May 26, 2015
    Publication date: December 17, 2015
    Inventors: Tomohiro Nakai, Susumu Kubota, Satoshi Ito, Tomoki Watanabe
  • Patent number: 9008434
    Abstract: According to one embodiment, a feature extraction device includes an obtaining unit that obtains image data having a plurality of pixels. The device includes a pixel feature calculation unit that calculates first pixel features and second pixel features of each of the pixels, which are different from each other, and a classification unit that classifies a pair of pixels by using the first features for at least some of the plurality of pixels. The device includes a co-occurrence frequency calculation unit that calculates a co-occurrence frequency representing a frequency of co-occurrence of the second pixel features of the first pixel and the second pixel features of the second pixel for the set for which a result of the classification by the classification unit is consistent.
    Type: Grant
    Filed: March 16, 2012
    Date of Patent: April 14, 2015
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Satoshi Ito, Susumu Kubota
  • Patent number: 9002101
    Abstract: According to an embodiment, a recognition device includes a generation unit to select, plural times, groups each including learning samples from a storage unit, learn a classification metric for classifying the groups selected in each selection, and generate an evaluation metric including the classification metrics; a transformation unit to transform a first feature value of an image including an object into a second feature value using the evaluation metric; a calculation unit to calculate similarities of the object to categories in a table using the second feature value and reference feature values; and a registration unit to register the second feature value as the reference feature value in the table associated with the category of the object and register the first feature value as the learning sample belonging to the category of the object in the storage unit. The generation unit performs the generation again.
    Type: Grant
    Filed: March 15, 2012
    Date of Patent: April 7, 2015
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Tomohiro Nakai, Toshimitsu Kaneko, Susumu Kubota, Satoshi Ito, Tatsuo Kozakaya
  • Patent number: 8890820
    Abstract: According to an embodiment, a control apparatus controls a touch panel includes a first resistive film includes a first terminal and a second terminal and a second resistive film includes a third terminal and a fourth terminal, the first and second resistive films being laid on top of each other with a gap between the resistive films. The control apparatus comprises an application unit, a measurement unit and a calculation unit. The application unit is configured to apply a voltage between the first terminal and the second terminal at a first timing. The measurement unit is configured to measure a voltage of each of the third and fourth terminals at the first timing. The calculation unit is configured to derive a positional relationship between two points at which the touch panel has been touched based on the voltages of the third and fourth terminals measured at the first timing.
    Type: Grant
    Filed: November 17, 2011
    Date of Patent: November 18, 2014
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Satoshi Ito, Susumu Kubota
  • Publication number: 20140177950
    Abstract: According to an embodiment, a recognition device includes a storage unit, an acquiring unit, a first calculator, a second calculator, a determining unit, and an output unit. The storage unit stores multiple training patterns each belonging to any one of multiple categories. The acquiring unit acquires a recognition target pattern to be recognized. The first calculator calculates, for each of the categories, a distance histogram representing distribution of the number of training patterns belonging to the category with respect to distances between the recognition target pattern and the training patterns belonging to the category. The second calculator analyzes the distance histogram of each of the categories to calculate confidence of the category. The determining unit determines a category of the recognition target pattern from the multiple categories by using the confidences. The output unit outputs the category of the recognition target pattern.
    Type: Application
    Filed: December 18, 2013
    Publication date: June 26, 2014
    Applicant: KABUSHIKI KAISHA TOSHIBA
    Inventors: Tomohiro Nakai, Susumu Kubota, Satoshi Ito
  • Publication number: 20140016017
    Abstract: According to an embodiment, an image processing device includes a generator and a processor. The generator is configured to generate, from a plurality of unit images in which points on an object are imaged by an imaging unit at different positions according to distances between the imaging unit and the positions of the points on the object, a refocused image focused at a predetermined distance. The processor is configured to perform blurring processing on each pixel of the refocused image according to an intensity corresponding to a focusing degree of the pixel of the refocused image.
    Type: Application
    Filed: July 9, 2013
    Publication date: January 16, 2014
    Inventors: Toshiyuki Ono, Yasunori Taguchi, Takuma Yamamoto, Susumu Kubota, Nobuyuki Matsumoto
  • Patent number: 8620066
    Abstract: According to one embodiment, a three-dimensional object determining apparatus includes: a detecting unit configured to detect a plurality of feature points of an object included in an image data that is acquired; a pattern normalizing unit configured to generate a normalized pattern that is normalized by a three-dimensional model from the image data using the plurality of feature points; an estimating unit configured to estimate an illumination direction in which light is emitted to the object in the image data from the three-dimensional model and the normalized pattern; and a determining unit configured to determine whether or not the object in the image data is a three-dimensional object on the basis of the illumination direction.
    Type: Grant
    Filed: September 15, 2011
    Date of Patent: December 31, 2013
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Tatsuo Kozakaya, Susumu Kubota
  • Publication number: 20130114888
    Abstract: According to an embodiment, an image processing apparatus includes a feature data calculator, a generating unit, and an adding unit. The feature data calculator calculates feature data representing changes in pixel values within a first range of an input image. The generating unit obtains a weight of a predetermined image pattern on the basis of a probability distribution and the feature data. The weight represents a pattern of changes in the pixel values. The probability distribution represents a distribution of relative values of feature data of a learning image containing a high-frequency component with respect to feature data of a learning image. The generating unit weights the predetermined image pattern with the weight so as to generate a high-frequency component with respect to the input image. The adding unit adds the high-frequency component to the input image.
    Type: Application
    Filed: November 7, 2012
    Publication date: May 9, 2013
    Inventors: Kanako SAITO, Toshimitsu KANEKO, Susumu KUBOTA, Yusuke MORIUCHI