Trainable Classifiers Or Pattern Recognizers (e.g., Adaline, Perceptron) Patents (Class 382/159)
  • Patent number: 9179201
    Abstract: Systems and methods of processing video streams are described. A face is detected in a video stream. The face is tracked to determine a video clip associated with one of a plurality of individuals. The video segment is assigned to a group of video clips based on the associated individual. A significant face is detected in the group of video clips when the detected face meets one or more significance criteria. The significance criteria describes a face-frame characteristic. A representation of the significant face is displayed in association with a representation of the group of video clips. The order of the significance criteria is adjusted through a user interface.
    Type: Grant
    Filed: August 26, 2011
    Date of Patent: November 3, 2015
    Assignee: CYBERLINK CORP.
    Inventors: Chen-Yu Chao, Shih-Hsien Yeh
  • Patent number: 9171226
    Abstract: Determining a match between the subjects of first and second images as a function of decimal-number representations of regions of the first and second images. The decimal-number representations are generated by performing discrete transforms on the regions so as to obtain discrete-transform coefficients, performing local-bit-pattern encoding of the coefficients to create data streams, and converting the data streams to decimal numbers. In one embodiment, the first and second images depict periocular facial regions, and the disclosed techniques can be used for face recognition, even where a small portion of a person's face is captured in an image. Subspace modeling may be used to improve accuracy.
    Type: Grant
    Filed: September 26, 2013
    Date of Patent: October 27, 2015
    Assignee: Carnegie Mellon University
    Inventors: Marios Savvides, Felix Juefei-Xu
  • Patent number: 9165216
    Abstract: Biometric data, which identifies a set of biometric patterns, is received from a set of biometric sensors. The biometric data is processed to form digital biometric data that identifies attributes of the biometric data. Thereafter, a biometric cohort is generated using the digital biometric data. Each member of the set of biometric cohorts shares at least one biometric attribute in common.
    Type: Grant
    Filed: February 10, 2012
    Date of Patent: October 20, 2015
    Assignee: International Business Machines Corporation
    Inventors: Robert L. Angell, Robert R. Friedlander, James R. Kraemer
  • Patent number: 9163940
    Abstract: A position/orientation measurement apparatus inputs the two-dimensional image of a measurement object captured by an image capturing apparatus, obtains the distance data of the measurement object measured by a distance sensor, detects an image feature of the measurement object from the two-dimensional image, determines the state of the measurement object, sets, based on the determined state, a usage mode regarding the image feature and the distance data when measuring the position/orientation, and measures the position/orientation of the measurement object in accordance with the set usage mode.
    Type: Grant
    Filed: July 14, 2011
    Date of Patent: October 20, 2015
    Assignee: Canon Kabushiki Kaisha
    Inventors: Masahiro Suzuki, Shinji Uchiyama
  • Patent number: 9152022
    Abstract: Techniques are disclosed for compensating for deficiencies of a given image projector so as to eliminate or otherwise reduce discrepancies between original image data provided to the projector and the actual image projected by the projector. The techniques also may be used to enhance an attribute of the original image data to improve the image projected by the projector. The techniques can be implemented, for instance, with an imaging capture device and an image comparison engine. In operation, the imaging capture device can capture a projected image from a viewing surface, and the image comparison engine can compare the original image data with the projected image captured by the imaging capture device. Based on the results of this comparison, an adjustment then can be made to achieve the desired projected image. The adjustment may entail, for example, adjusting the original image data provided to the projector and/or adjusting projector settings.
    Type: Grant
    Filed: July 11, 2013
    Date of Patent: October 6, 2015
    Assignee: INTEL CORPORATION
    Inventor: Michael Stahl
  • Patent number: 9152746
    Abstract: A quantum annealer simulator approximates unitary quantum dynamics of a quantum annealer on a non-quantum computing device such as a conventional computing device. The quantum annealer simulator may utilize algorithms that may efficiently approximate unitary time evolution of a quantum system, where the quantum system corresponds to a problem for which an optimized solution is sought.
    Type: Grant
    Filed: March 26, 2013
    Date of Patent: October 6, 2015
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Matthias Troyer, David B. Wecker, Bela Bauer
  • Patent number: 9141852
    Abstract: A system for detecting a person and estimating pose information comprises a processor and a memory storing instructions causing the system to: retrieve depth data from a sensor, the depth data describing distance information associated with one or more objects detected by the sensor; cluster the depth data to determine two or more candidate leg clusters, each candidate leg cluster including a portion of the depth data that may represent a human leg detected by the sensor; identify a candidate leg cluster pair including two candidate leg clusters within a certain distance between each other; determine whether there is a connectivity between the two candidate leg clusters included in the candidate leg cluster pair; and responsive to determining that there is a connectivity between the two candidate leg clusters, determine that the candidate leg cluster pair is qualified to be a leg cluster pair representing a person.
    Type: Grant
    Filed: August 28, 2013
    Date of Patent: September 22, 2015
    Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA
    Inventors: Akansel Cosgun, Emrah Akin Sisbot
  • Patent number: 9135525
    Abstract: A character recognition apparatus includes an evaluation-value output unit, a generation unit, a learning unit, and a determination unit. The evaluation-value output unit outputs evaluation values for each of different character recognition programs. Each evaluation value indicates a degree to which an inputted character pattern corresponds to each of character codes to be recognized using the character recognition program. The generation unit generates feature information for the character pattern. The feature information includes, as elements, the evaluation values. The learning unit learns classifications for feature information on a character-code-by-character-code basis based on feature information generated for a character pattern for which a character code is specified in advance.
    Type: Grant
    Filed: May 17, 2013
    Date of Patent: September 15, 2015
    Assignee: FUJI XEROX CO., LTD.
    Inventor: Hideto Oda
  • Patent number: 9135696
    Abstract: The pose of an implant represented in a medical image is determined from the medical image. The x-ray image of the implant is compared to a database of the implant viewed at different poses (e.g., viewed from different directions). The implant pose associated with the best match indicates the pose of the implant in the x-ray image.
    Type: Grant
    Filed: January 7, 2013
    Date of Patent: September 15, 2015
    Assignee: Siemens Aktiengesellschaft
    Inventors: Shaolei Feng, Shaohua Kevin Zhou, Gerhard Kleinszig, Rainer Graumann
  • Patent number: 9124741
    Abstract: An electronic device in the present disclosure includes the following: an imaging device configured to scan a paper sheet, wherein the paper sheet comprises a first side and a second side, wherein scanning the paper sheet produces an image; a display device; a printing image acquisition unit configured to acquire a printing image; an image forming apparatus configured to print the printing image; and a display control unit configured to control the display device to display, if the produced image includes an image of a paper sheet, a composite image that combines the acquired printing image and the image of the paper sheet within the produced image.
    Type: Grant
    Filed: April 29, 2014
    Date of Patent: September 1, 2015
    Assignee: KYOCERA Document Solutions Inc.
    Inventor: Makoto Kowaka
  • Patent number: 9122950
    Abstract: Disclosed herein are techniques for enhancing the accuracy of atlas-based auto-segmentation (ABAS) using an automated structure classifier that was trained using a machine learning algorithm. Also disclosed is a technique for training the automated structure classifier using atlas data applied to the machine learning algorithm.
    Type: Grant
    Filed: March 1, 2013
    Date of Patent: September 1, 2015
    Assignee: IMPAC MEDICAL SYSTEMS, INC.
    Inventor: Xiao Han
  • Patent number: 9117146
    Abstract: Systems and methods for modeling the occurrence of common image components (e.g., sub-regions) in order to improve visual object recognition are disclosed. In one example, a query image may be matched to a training image of an object. A matched region within the training image to which the query image matches may be determined and a determination may be made whether the matched region is located within an annotated image component of the training image. When the matched region matches only to the image component, an annotation associated with the component may be identified. In another example, sub-regions within a plurality of training image corpora may be annotated as common image components including associated information (e.g., metadata). Matching sub-regions appearing in many training images of objects may be down-weighted in the matching process to reduce possible false matches to query images including common image components.
    Type: Grant
    Filed: December 31, 2013
    Date of Patent: August 25, 2015
    Assignee: Google Inc.
    Inventors: Yuan Li, Hartwig Adam
  • Patent number: 9104911
    Abstract: A method and apparatus for processing an observation of an object to be classified, the method comprising using a particle filter in which an observation of an object to be classified is used to weight particles on a plurality of models for the object. The method may further comprise performing at least one further iteration of using the particle filter to weight the particles on the plurality of models for the object using a further observation of the object to be classified. The method may further comprise providing respective classification probabilities that each respective model corresponds to the object based on the weightings of the particles of the respective model. Each of the respective particles may be divided into a respective plurality of sub-particles.
    Type: Grant
    Filed: May 13, 2010
    Date of Patent: August 11, 2015
    Assignee: BAE SYSTEMS PLC
    Inventors: Jordi McGregor Barr, Christopher Mark Lloyd, David Nicholson, Mark Lawrence Williams
  • Patent number: 9087379
    Abstract: An apparatus and method for estimating a pose of an object are provided. The apparatus includes an object input unit configured to input an object in an object tracking unit and an object identifying unit, an object tracking unit configured to obtain a tracked pose probability density of the object based on a tracking scheme, an object identifying unit configured to obtain an identified pose probability density of the object based on a training model, and a combination unit configured to obtain an estimated pose probability density of the object using a combination of the tracked pose probability density and the identified pose probability density and to estimate a pose of the object based on the estimated pose probability density of the object. Through the combination, a cumulative error occurring in the object tracking may be corrected, resulting in more accurate object estimation.
    Type: Grant
    Filed: December 21, 2012
    Date of Patent: July 21, 2015
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Xiying Wang, Shuzheng Gao
  • Patent number: 9082048
    Abstract: Systems and methods for authenticating a user are disclosed. In some embodiments, information regarding multiple biometric parameters is gathered from a test subject and compared with a validation template. The validation template can be augmented with some or all of the information if the user is successfully authenticated.
    Type: Grant
    Filed: February 9, 2012
    Date of Patent: July 14, 2015
    Assignee: CONVERGENCE BIOMETRICS, LLC
    Inventor: David R. Miller
  • Patent number: 9076081
    Abstract: A multi-class discriminating device for judging to which class a feature represented by data falls. The device has a first unit for generating plural first hierarchical discriminating devices for discriminating one from N, and a second unit for combining score values output respectively from the plural first hierarchical discriminating devices to generate a second hierarchical feature vector and for entering the second hierarchical feature vector to generate plural second hierarchical discriminating devices for discriminating one from N. When data is entered, the plural first hierarchical discriminating devices output score values, and these score values are combined together to generate the second hierarchical feature vector. When the second hierarchical feature vector is entered, the second hierarchical discriminating device which outputs the maximum score value is selected.
    Type: Grant
    Filed: October 25, 2013
    Date of Patent: July 7, 2015
    Assignee: CASIO COMPUTER CO., LTD.
    Inventors: Kazuhisa Matsunaga, Kouichi Nakagome, Michihiro Nihei, Masayuki Hirohama
  • Patent number: 9053392
    Abstract: A hierarchy machine may be configured as a clustering machine that utilizes local feature embedding to organize visual patterns into nodes that each represent one or more visual patterns. These nodes may be arranged as a hierarchy in which a node may have a parent-child relationship with one or more other nodes. The hierarchy machine may implement a node splitting and tree-learning algorithm that includes hard-splitting of nodes and soft-assignment of nodes to perform error-bounded splitting of nodes into clusters. This may enable the hierarchy machine, which may form all or part of a visual pattern recognition system, to perform large-scale visual pattern recognition, such as font recognition or facial recognition, based on a learned error-bounded tree of visual patterns.
    Type: Grant
    Filed: August 28, 2013
    Date of Patent: June 9, 2015
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Jianchao Yang, Guang Chen, Hailin Jin, Jonathan Brandt, Elya Shechtman
  • Patent number: 9053434
    Abstract: A technique for determining an obverse weight. A set of cases can be divided into bins. An obverse weight for a bin can be determined based on an importance weight of the bin and a variance of an error estimate of the bin.
    Type: Grant
    Filed: March 15, 2013
    Date of Patent: June 9, 2015
    Assignee: Hewlett-Packard Development Company, L.P.
    Inventor: George Forman
  • Publication number: 20150146974
    Abstract: An image processing apparatus includes a first acquiring unit that acquires an image to be processed; a setting unit that sets multiple partial image areas in the image to be processed; a second acquiring unit that acquires a first classification result indicating a possibility that an object of a specific kind is included in each of the multiple partial image areas; and a generating unit that generates a second classification result indicating a possibility that the object of the specific kind is included in the image to be processed on the basis of the first classification result of each of the multiple partial image areas.
    Type: Application
    Filed: June 5, 2014
    Publication date: May 28, 2015
    Applicant: FUJI XEROX CO., LTD
    Inventor: Noriji KATO
  • Publication number: 20150146973
    Abstract: A system and method for distributed similarity learning for high-dimensional image features are described. A set of data features is accessed. Subspaces from a space formed by the set of data features are determined using a set of projection matrices. Each subspace has a dimension lower than a dimension of the set of data features. Similarity functions are computed for the subspaces. Each similarity function is based on the dimension of the corresponding subspace. A linear combination of the similarity functions is performed to determine a similarity function for the set of data features.
    Type: Application
    Filed: November 27, 2013
    Publication date: May 28, 2015
    Applicant: Adobe Systems Incorporated
    Inventors: Jianchao Yang, Zhaowen Wang, Zhe Lin, Jonathan Brandt
  • Patent number: 9042641
    Abstract: A character recognition apparatus includes an extracting unit extracting a feature point for a line in a handwritten character, first and second generation units, a learning unit, and a determination unit. The first generation unit generates first feature data from feature points for lines including an in-same-character line (first line) and being selected from lines in character-code-specified handwritten characters (known lines). The second generation unit generates second feature data from feature points for lines including an after-character-transition line (second line) and being selected from known lines. The learning unit causes a discriminator to learn classifications for first and second lines based on the first and second feature data. The determination unit determines whether each line in character-code-unknown handwritten characters is a first or second line, based on which classification is determined by the discriminator for feature data for the line.
    Type: Grant
    Filed: May 28, 2013
    Date of Patent: May 26, 2015
    Assignee: FUJI XEROX CO., LTD.
    Inventor: Hideto Oda
  • Patent number: 9042640
    Abstract: As set forth herein, a computer-implemented method facilitates pre-analyzing an image and automatically suggesting to the user the most suitable regions within an image for text-based personalization. Image regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are primary candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Smooth regions are found by dividing the image into blocks and applying an iterative combining strategy, and those regions satisfying certain spatial properties (e.g. size, position, shape of the boundary) are retained as promising candidates. In one embodiment, connected component analysis is performed on the image for locating text regions. Finally, based on the smooth and text regions found in the image, several alternative approaches are described herein to derive an overall metric for “suitability for personalization.
    Type: Grant
    Filed: January 13, 2012
    Date of Patent: May 26, 2015
    Assignee: XEROX CORPORATION
    Inventors: Raja Bala, Zhigang Fan, Hengzhou Ding, Jan P. Allebach, Charles A. Bouman, Reuven J. Sherwin
  • Publication number: 20150142708
    Abstract: Methods, systems, and articles of manufacture for annotating of an image are disclosed. These include scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels; selecting one or more of the image groups based upon the scoring; aggregating one or more sets of weighted labels associated with the selected one or more image groups; and annotating the image using the aggregated one or more sets of weighted labels.
    Type: Application
    Filed: November 6, 2014
    Publication date: May 21, 2015
    Applicant: Google Inc.
    Inventors: Yushi JING, Yi Liu, David Tsai
  • Publication number: 20150139538
    Abstract: In techniques for object detection with boosted exemplars, weak classifiers of a real-adaboost technique can be learned as exemplars that are collected from example images. The exemplars are examples of an object that is detectable in image patches of an image, such as faces that are detectable in images. The weak classifiers of the real-adaboost technique can be applied to the image patches of the image, and a confidence score is determined for each of the weak classifiers as applied to an image patch of the image. The confidence score of a weak classifier is an indication of whether the object is detected in the image patch of the image based on the weak classifier. All of the confidence scores of the weak classifiers can then be summed to generate an overall object detection score that indicates whether the image patch of the image includes the object.
    Type: Application
    Filed: November 15, 2013
    Publication date: May 21, 2015
    Applicant: Adobe Systems Incorporated
    Inventors: Zhe Lin, Jonathan W. Brandt, Xiaohui Shen, Haoxiang Li
  • Patent number: 9036904
    Abstract: There is provided an image processing device including a weight calculation unit that calculates a weight corresponding to each of a plurality of pixel values centering on a pixel of interest of an input image based on a feature amount calculated based on the plurality of pixel values centering on the pixel of interest, a regression coefficient reading unit that reads a regression coefficient stored for each class code determined based on a plurality of pixel values corresponding to the pixel of interest of the input image, and a pixel value calculation unit that calculates a pixel value of a pixel of interest of an output image by performing calculation using the plurality of pixel values, the weights, and the regression coefficients centering on the pixel of interest of the input image.
    Type: Grant
    Filed: May 10, 2013
    Date of Patent: May 19, 2015
    Assignee: Sony Corporation
    Inventors: Kenichiro Hosokawa, Takahiro Nagano, Shintaro Okada, Yiwen Zhu, Kazunori Kamio
  • Patent number: 9036903
    Abstract: A learning device includes a gradient feature extraction unit which extracts a gradient feature amount including a gradient direction at each coordinate and a gradient intensity value thereof based on an amount of variation between luminance at each coordinate of an inputted learning target pattern and luminance at a periphery thereof, a sum difference feature extraction unit which calculates a predetermined sum difference feature amount by adding the gradient intensity values according to the gradient directions included in a predetermined gradient range indicating a range of the predetermined gradient direction based on the extracted gradient feature amount and subtracting the gradient intensity values according to the gradient directions included in the other gradient range adjacent to the predetermined gradient range from the calculated sum, and a learning unit which acquires a learning parameter at each coordinate.
    Type: Grant
    Filed: December 24, 2010
    Date of Patent: May 19, 2015
    Assignee: NEC CORPORATION
    Inventor: Toshinori Hosoi
  • Patent number: 9036905
    Abstract: A classifier training system trains a classifier for evaluating image deblurring quality using a set of scored deblurred images. In some embodiments, the classifier training system trains the classifier based on a number of sub-images extracted from the scored deblurred images. An image deblurring system applies a number of different deblurring transformations to a given blurry reference image and uses the classifier trained by the classifier training system to evaluate deblurring quality, thereby finding a highest-quality deblurred image. In some embodiments, the classifier training system trains the classifier in the frequency domain, and the image deblurring system uses the classifier trained by the classifier training system to evaluate deblurring quality in the frequency domain. In some embodiments, the image deblurring system applies the different deblurring transformations iteratively.
    Type: Grant
    Filed: September 11, 2014
    Date of Patent: May 19, 2015
    Assignee: Google Inc.
    Inventor: Hui Fang
  • Patent number: 9036924
    Abstract: Method for classifying a two- or higher dimensional image, where each pixel is associated with M property measures, includes identifying firstly a certain predetermined, variable geometric structure, the extension of which in at least two of the N dimensions in the dataset is determined in relation to a single element in the dataset and by at least one variable parameter, and secondly at least one geometric measure associated with the variable geometric structure, which geometric measure is arranged to measure a geometric property of a specific geometric structure in relation to other specific such geometric structures, and in that a main classification is conducted of the dataset, which main classification is based upon a comparative measure between the respective sets of associated geometric measures of two elements, calculated from a respective maximal geometric structure for each element.
    Type: Grant
    Filed: September 9, 2011
    Date of Patent: May 19, 2015
    Assignee: Choros Cognition AB
    Inventors: Anders Brun, Zihan Hans Liu, Anders Wästfelt, Bo Malmberg, Michael Nielsen
  • Patent number: 9036902
    Abstract: This specification generally relates to methods and algorithms for detection of chemical, biological, and/or radiological attacks. The methods use one or more sensors that can have visual, audio, and/or thermal sensing abilities and can use algorithms to determine by behavior patterns of people whether there has been a chemical, biological and/or radiological attack.
    Type: Grant
    Filed: March 1, 2011
    Date of Patent: May 19, 2015
    Assignee: INTELLIVISION TECHNOLOGIES CORPORATION
    Inventors: Anoo Nathan, Chandan Gope, Albert Kay
  • Publication number: 20150131899
    Abstract: Systems, devices, and methods for generating an image representation obtain a set of low-level features from an image; generate a high-dimensional generative representation of the low-level features; generate a lower-dimensional representation of the low-level features based on the high-dimensional generative representation of the low-level features; generate classifier scores based on classifiers and on one or more of the high-dimensional generative representation and the lower-dimensional representation, wherein each classifier uses the one or more of the high-dimensional generative representation and the lower-dimensional representation as an input, and wherein each classifier is associated with a respective label; and generate a combined representation for the image based on the classifier scores and the lower-dimensional representation.
    Type: Application
    Filed: November 13, 2013
    Publication date: May 14, 2015
    Inventors: Juwei Lu, Daruisz T. Dusberger, Bradley Scott Denney
  • Publication number: 20150131898
    Abstract: Blind image deblurring with a cascade architecture is described, for example, where photographs taken on a camera phone are deblurred in a process which revises blur estimates and estimates a blur function as a combined process. In various examples the estimates of the blur function are computed using first trained machine learning predictors arranged in a cascade architecture. In various examples a revised blur estimate is calculated at each level of the cascade using a latest deblurred version of a blurred image. In some examples the revised blur estimates are calculated using second trained machine learning predictors interleaved with the first trained machine learning predictors.
    Type: Application
    Filed: November 12, 2013
    Publication date: May 14, 2015
    Applicant: Microsoft Corporation
    Inventors: Kevin Schelten, Reinhard Sebastian Bernhard Nowozin, Jeremy Jancsary, Carsten Curt Eckard Rother
  • Publication number: 20150131900
    Abstract: Software for supervised learning extracts a set of pixel-level features from each source image in collection of source images. Each of the source images is associated with a thumbnail created by an editor. The software also generates a collection of unique bounding boxes for each source image. And the software calculates a set of region-level features for each bounding box. Each region-level feature results from the aggregation of pixel values for one of the pixel-level features. The software learns a regression model, using the calculated region-level features and the thumbnail associated with the source image. Then the software chooses a thumbnail from a collection of unique bounding boxes in a new image, based on application of the regression model. The software uses a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold.
    Type: Application
    Filed: January 16, 2015
    Publication date: May 14, 2015
    Inventors: Lyndon Kennedy, Roelof van Zwol, Nicolas Torzec, Belle Tseng
  • Patent number: 9031331
    Abstract: A classification system and method enable improvements to classification with nearest class mean classifiers by computing a comparison measure between a multidimensional representation of a new sample and a respective multidimensional class representation embedded into a space of lower dimensionality than that of the multidimensional representations. The embedding is performed with a projection that has been learned on labeled samples to optimize classification with respect to multidimensional class representations for classes which may be the same or different from those used subsequently for classification. Each multidimensional class representation is computed as a function of a set of multidimensional representations of labeled samples, each labeled with the respective class. A class is assigned to the new sample based on the computed comparison measures.
    Type: Grant
    Filed: July 30, 2012
    Date of Patent: May 12, 2015
    Assignee: Xerox Corporation
    Inventors: Thomas Mensink, Jakob Verbeek, Gabriela Csurka, Florent Perronnin
  • Patent number: 9031317
    Abstract: An adequate solution for computer vision applications is arrived at more efficiently and, with more automation, enables users with limited or no special image processing and pattern recognition knowledge to create reliable vision systems for their applications. Computer rendering of CAD models is used to automate the dataset acquisition process and labeling process. In order to speed up the training data preparation while maintaining the data quality, a number of processed samples are generated from one or a few seed images.
    Type: Grant
    Filed: September 18, 2012
    Date of Patent: May 12, 2015
    Assignee: Seiko Epson Corporation
    Inventors: Yury Yakubovich, Ivo Moravec, Yang Yang, Ian Clarke, Lihui Chen, Eunice Poon, Mikhail Brusnitsyn, Arash Abadpour, Dan Rico, Guoyi Fu
  • Publication number: 20150125073
    Abstract: A method of processing an image by using an image processing apparatus is provided. The method includes acquiring, by the image processing apparatus, a target image, extracting a shape of a target object included in the target image, determining a category including the target object based on the extracted shape, and storing the target image by mapping the target image with additional information including at least one keyword related to the category.
    Type: Application
    Filed: November 4, 2014
    Publication date: May 7, 2015
    Inventors: Seong-taek HWANG, Sang-doo YUN, Ha-wook JEONG, Jin-young CHOI, Byeong-ho HEO, Woo-sung KANG
  • Patent number: 9025864
    Abstract: The disclosure relates to a system and a method for generating clothing feature data representative of at least one clothing feature of a piece of clothing being worn by the person in a set of images, and training a discriminative clothing classifier using the clothing feature data to provide a personal clothing model that corresponds to the piece of clothing. The personal clothing model can be used to identify additional images in which the person appears.
    Type: Grant
    Filed: August 2, 2010
    Date of Patent: May 5, 2015
    Assignee: Hewlett-Packard Development Company, L.P.
    Inventors: Tong Zhang, Wei Zhang, Daniel R Tretter
  • Patent number: 9025866
    Abstract: A method of operating a computer system to perform material recognition based on multiple features extracted from an image is described. A combination of low-level features extracted directly from the image and multiple novel mid-level features extracted from transformed versions of the image are selected and used to assign a material category to a single image. The novel mid-level features include non-reflectance based features such as the micro-texture features micro-jet and micro-SIFT and the shape feature curvature, and reflectance-based features including edge slice and edge ribbon. An augmented Latent Dirichlet Allocation (LDA) model is provided as an exemplary Bayesian framework for selecting a subset of features useful for material recognition of objects in an image.
    Type: Grant
    Filed: June 27, 2013
    Date of Patent: May 5, 2015
    Assignee: Microsoft Technology Licensing, LLC
    Inventor: Ce Liu
  • Patent number: 9025863
    Abstract: Generally, this disclosure provides systems, devices, methods and computer readable media for a depth camera with ML techniques for recognition of patches within an SL pattern. The system may include a projection module to project an ML-based SL pattern onto a scene; a camera to receive an image of the SL pattern reflected from the scene; a patch recognition and location module to generate a descriptor vector for a patch segmented from the received image and to query an ML system with the descriptor vector, the ML system configured to provide a patch label associated with the descriptor vector, the patch label comprising a location of the patch relative to the projected SL pattern; and a depth estimation module to triangulate a distance between the camera and a region of the scene associated with the patch based on the location of the patch relative to the projected SL pattern.
    Type: Grant
    Filed: June 27, 2013
    Date of Patent: May 5, 2015
    Assignee: Intel Corporation
    Inventor: Dror Reif
  • Patent number: 9025865
    Abstract: Methods and systems for reducing the required footprint of SNoW-based classifiers via optimization of classifier features. A compression technique involves two training cycles. The first cycle proceeds normally and the classifier weights from this cycle are used to rank the Successive Mean Quantization Transform (SMQT) features using several criteria. The top N (out of 512 features) are then chosen and the training cycle is repeated using only the top N features. It has been found that OCR accuracy is maintained using only 60 out of 512 features leading to an 88% reduction in RAM utilization at runtime. This coupled with a packing of the weights from doubles to single byte integers added a further 8× reduction in RAM footprint or a reduction of 68× over the baseline SNoW method.
    Type: Grant
    Filed: January 22, 2013
    Date of Patent: May 5, 2015
    Assignee: Xerox Corporation
    Inventors: Vladimir Kozitsky, Aaron Michael Burry, Peter Paul
  • Publication number: 20150117764
    Abstract: Methods and systems for distance metric learning include generating two random projection matrices of a dataset from a d-dimensional space into an m-dimensional sub-space, where m is smaller than d. An optimization problem is solved in the m-dimensional subspace to learn a distance metric based on the random projection matrices. The distance metric is recovered in the d-dimensional space.
    Type: Application
    Filed: October 27, 2014
    Publication date: April 30, 2015
    Inventors: Shenghuo Zhu, Yuanqing Lin, Qi Qian
  • Publication number: 20150117762
    Abstract: Provided is an image processing device that can bring about the sufficient resemblance between an original image and a restored image obtained corresponding to a low resolution input image. The image processing device includes a means that uses a dictionary for storing data associating deteriorated patches which are from a deteriorated image formed by deteriorating a prescribed image, and restoration patches which are from the prescribed image, and calculates, as a degree-of-similarity between plural input patches generated by dividing an input image and the deteriorated patches, a weighted degree-of-similarity between weighted deteriorated patches and weighted input patches, in which forms of the deteriorated patches and the input patches are reconfigured using a patch weight which is continuous weighting; a means that selects, on the basis of the weighted degree-of-similarity, a restoration patch for each input patch; and a means that combines the restoration patches to generate a restored image.
    Type: Application
    Filed: December 10, 2012
    Publication date: April 30, 2015
    Applicant: NEC Corporation
    Inventors: Takashi Shibata, Akihiko Iketani, Shuji Senda
  • Publication number: 20150117765
    Abstract: Data from one or more sensors is input to a workflow and fragmented to produce HyperFragments. The HyperFragments of input data are processed by a plurality of Distributed Experts, who make decisions about what is included in the HyperFragments or add details relating to elements included therein, producing tagged HyperFragments, which are maintained as tuples in a Semantic Database. Algorithms are applied to process the HyperFragments to create an event definition corresponding to a specific activity. Based on related activity included in historical data and on ground truth data, the event definition is refined to produce a more accurate event definition. The resulting refined event definition can then be used with the current input data to more accurately detect when the specific activity is being carried out.
    Type: Application
    Filed: November 25, 2014
    Publication date: April 30, 2015
    Inventor: Nils B. Lahr
  • Publication number: 20150117763
    Abstract: A method and system for determining a quality metric score for image processing are described including accepting a reference image, performing a pyramid transformation on the accepted reference image to produce a predetermined number of scales, applying image division to each scale to produce reference image patches, accepting a distorted image, performing a pyramid transformation on the accepted distorted image to produce the predetermined number of scales, applying image division to each scale to produce distorted image patches, performing a local distortion calculation for corresponding reference and distorted image patches, summing local distortion calculation results for image patch pairs, multiplying results of the summation operation by a positive weight for each scale, summing the results of the multiplication operation and applying a sigmoid function to results of the second summation operation to produce the quality metric score.
    Type: Application
    Filed: May 31, 2012
    Publication date: April 30, 2015
    Applicant: THOMSON LICENSING
    Inventors: Fan Zhang, Zhibo Chen, Wenfei Jiang
  • Publication number: 20150117761
    Abstract: The invention discloses an image processing method and an imager processing apparatus using the same. The method includes the following steps: receiving an training image; finding a minimum difference among the differences; determining whether the minimum difference is larger than a first threshold; if no, generating a first output value according to the first pixel, the background candidates and a plurality of weightings corresponding to the background candidates; updating a first background candidate corresponding to the minimum difference; updating a first weighting related to the first background candidate; if yes, adding the first pixel as a new background candidate to the background candidates and adding a new weighting corresponding to the new background candidate to the weightings; and detecting whether a moving object existing in an incoming image according to the background candidates and the weightings.
    Type: Application
    Filed: October 29, 2013
    Publication date: April 30, 2015
    Applicant: National Taipei University of Technology
    Inventors: Shih-Chia Huang, Bo-Hao Chen
  • Patent number: 9020244
    Abstract: Techniques are described herein for selecting representative images for video items using a trained machine learning engine. A training set is fed to a machine learning engine. The training set includes, for each image in the training set, input parameter values and an externally-generated score. Once a machine learning model has been generated based on the training set, input parameters for unscored images are fed to the trained machine learning engine. Based on the machine learning model, the trained machine learning engine generates scores for the images. To select a representative image for a particular video item, candidate images for that particular video item may be ranked based on their scores, and the candidate image with the top score may be selected as the representative image for the video item.
    Type: Grant
    Filed: December 6, 2011
    Date of Patent: April 28, 2015
    Assignee: Yahoo! Inc.
    Inventors: Roelof van Zwol, Lluis Garcia Pueyo
  • Patent number: 9020245
    Abstract: A training device comprises a first regenerating unit regenerates at least one of an image and a voice for training during the training courses which lead the user to train the operation of an input device, an operation accepting unit accepts the user operation for at least one of the image and the voice for training from a simulated user interface which simulates a user interface of the input device during training, a second regenerating unit regenerates at least one of the image and the voice for training when the training is ended, and a normal operation instructing unit instructs a normal operation to the user by outputting at least one of the image and the voice of the normal operation of the user, which show at least one of the image and the voice for training, which is synchronous with the regeneration of the second regenerating unit.
    Type: Grant
    Filed: February 7, 2012
    Date of Patent: April 28, 2015
    Assignee: Toshiba Tec Kabushiki Kaisha
    Inventors: Daigo Kudou, Masanori Sambe, Takesi Kawaguti
  • Patent number: 9019278
    Abstract: Systems, methods and products for animating non-humanoid characters with human motion are described. One aspect includes selecting key poses included in initial motion data at a computing system; obtaining non-humanoid character key poses which provide a one to one correspondence to selected key poses in said initial motion data; and statically mapping poses of said initial motion data to non-humanoid character poses using a model built based on said one to one correspondence from said key poses of said initial motion data to said non-humanoid character key poses. Other embodiments are described.
    Type: Grant
    Filed: December 2, 2013
    Date of Patent: April 28, 2015
    Assignee: Disney Enterprises, Inc.
    Inventors: Jessica Kate Hodgins, Katsu Yamane, Yuka Ariki
  • Patent number: 9020246
    Abstract: Systems and methods for improving visual object recognition by analyzing query images are disclosed. In one example, a visual object recognition module may determine query images matching objects of a training corpus utilized by the module. Matched query images may be added to the training corpus as training images of a matched object to expand the recognition of the object by the module. In another example, relevant candidate image corpora from a pool of image data may be automatically selected by matching the candidate image corpora against user query images. Selected image corpora may be added to a training corpus to improve recognition coverage. In yet another example, objects unknown to a visual object recognition module may be discovered by clustering query images. Clusters of similar query images may be annotated and added into a training corpus to improve recognition coverage.
    Type: Grant
    Filed: October 3, 2013
    Date of Patent: April 28, 2015
    Assignee: Google Inc.
    Inventors: Yuan Li, Hartwig Adam
  • Patent number: 9020211
    Abstract: A data processing apparatus which sequentially executes a verification process so as to recognize a target object, comprising: an obtaining unit configured to obtain dictionary data to be referred to in the verification process; a holding unit configured to hold a plurality of dictionary data; a verification unit configured to execute the verification process for the input data by referring to one dictionary data; a history holding unit configured to hold a verification result; and a prefetch determination unit configured to determine based on the verification result whether to execute prefetch processing in which the obtaining unit obtains in advance dictionary data to be referred to by the verification unit in a succeeding verification process, and holds the dictionary data in the holding unit before the succeeding verification process.
    Type: Grant
    Filed: May 10, 2012
    Date of Patent: April 28, 2015
    Assignee: Canon Kabushiki Kaisha
    Inventor: Akiyoshi Momoi
  • Patent number: 9020276
    Abstract: A hardware coprocessor architecture calculates the Difference-of-Gaussian (DoG) pyramid of an input image and extracts from this the interest points to be used in several image detection algorithms. Advantages of the architecture include the possibility to process the image by stripes, namely by blocks having one dimension coincident with the input image width, in the absence of an input frame buffer and the possibility to avoid RAM memory. The coprocessor is suitable to be tightly coupled with raw image sources like sensors.
    Type: Grant
    Filed: April 24, 2013
    Date of Patent: April 28, 2015
    Assignee: STMicroelectronics S.r.l.
    Inventors: Mario Vigliar, Gian Domenico Licciardo