Patent application number | Description | Published |
20090060290 | FACE IMAGE PROCESSING APPARATUS, FACE IMAGE PROCESSING METHOD, AND COMPUTER PROGRAM - A face image processing apparatus selects feature points and feature for identifying a person through statistical learning. The apparatus includes input means for inputting a face image detected by arbitrary face detection means, face parts detection means for detecting the positions of face parts in several locations from the input face image, face pose estimation means for estimating face pose based on the detected positions of face parts, feature point position correcting means for correcting the position of each feature point used for identifying the person based on the result of estimation of face pose by the face pose estimation means, and face identifying means for identifying the person by calculating a feature of the input face image at each feature point after position correction is performed by the feature point position correcting means and checking the feature against a feature of a registered face. | 03-05-2009 |
20090150317 | Information processing apparatus, information processing method and program - An information processing apparatus includes a target storage means, a control means, a decision means, a prediction means and a generating means, in which the decision means, when determining that the system state makes a transition to a state represented by the target value in accordance with the output of the time series of motor signals generated by the generating means, updates a parameter representing the relationship between input and output, which is used by the control means for controlling the system based on the time series of motor signals generated by the generating means and a time series of sensor signals observed in accordance with the output of the time series of motor signals. | 06-11-2009 |
20090202145 | LEARNING APPARTUS, LEARNING METHOD, RECOGNITION APPARATUS, RECOGNITION METHOD, AND PROGRAM - A learning apparatus includes: first feature quantity calculating means for pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and first discriminator generating means for generating a first discriminator for detecting the target object from an image by a statistical learning using a plurality of the first feature quantities. | 08-13-2009 |
20100055654 | Learning Apparatus, Learning Method, Recognition Apparatus, Recognition Method, and Program - A learning apparatus includes a feature extractor for extracting a feature at a feature point in a plurality of training images including training images that contains a target object to be recognized and that does not contain the target object, a tentative learner generator for generating a tentative learner for detecting the target object in an image, where the tentative learner is formed from a plurality of weak learners through statistical learning using the training images and the feature obtained from the training images, and a learner generator for generating a final learner that is formed from at least one of the weak learners and that detects the target object in an image by substituting the feature into a feature function formed from some of the weak learners of the tentative learner so as to obtain a new feature and performing statistical learning using the new feature and training images. | 03-04-2010 |
20100086175 | Image Processing Apparatus, Image Processing Method, Program, and Recording Medium - An image processing apparatus includes a detector, a setting unit, and an image generator. The detector detects a target object image region from a first image. When one or more predetermined parameters are applicable to a target object within the region detected by the detector, the setting unit sets the relevant target object image region as a first region. The image generator then generates a second image by applying predetermined processing to either the image portion within the first region, or to the image portions in a second region containing image portions within the first image that are not contained in the first region. | 04-08-2010 |
20100086176 | Learning Apparatus and Method, Recognition Apparatus and Method, Program, and Recording Medium - A learning apparatus includes an image generator, a feature point extractor, a feature value calculator, and a classifier generator. The image generator generates, from an input image, images having differing scale coefficients. The feature point extractor extracts feature points from each image generated by the image generator. The feature value calculator calculates feature values for the feature points by filtering the feature points using a predetermined filter. The classifier generator generates one or more classifiers for detecting a predetermined target object from an image by means of statistical learning using the feature values. | 04-08-2010 |
20100188519 | Information Processing Device and Method, Program, and Recording Medium - An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation. | 07-29-2010 |
20100245394 | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM - An image processing apparatus detects a representative frame of a moving image. The image processing apparatus includes a holding section configured to hold the moving image which is inputted, a detecting section configured to detect a peak of zooming that occurs in the inputted moving image, and an extracting section configured to extract the representative frame corresponding to the detected peak from a plurality of frames constituting the held moving image. | 09-30-2010 |
20100246908 | Image Processing Apparatus, Image Processing Method, and Program - An image processing apparatus identifies tissues in respective parts of a tissue image. A tissue image subdivider subdivides a tissue image for identification into local regions. A detector detects texture feature values of the local regions. A determining unit compares the detected texture feature value of a local region to a learned feature value for identification associated with a predetermined tissue, and on the basis of the comparison result, determines whether or not the local region belongs to the predetermined tissue. | 09-30-2010 |
20100290700 | INFORMATION PROCESSING DEVICE AND METHOD, LEARNING DEVICE AND METHOD, PROGRAMS, AND INFORMATION PROCESSING SYSTEM - An information processing device including an extraction unit and a detection unit. If both a parameter set extracting features from an image and a classifier performing predetermined classification by using the extracted features are statistically learned in advance, the extraction unit extracts features of a recognition target object from an input image by using the parameter set, and the detection unit performs the predetermined classification by using the classifier, which uses the features extracted by the extraction unit, and, on the basis of the result of the classification, determines whether or not the object is included in the input image. | 11-18-2010 |
20110029465 | DATA PROCESSING APPARATUS, DATA PROCESSING METHOD, AND PROGRAM - A data processing apparatus includes an obtaining unit configured to obtain time-series data from a wearable sensor, an activity model learning unit configured to learn an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit configured to recognize a current user activity state by using the activity model of the user obtained by the activity model learning unit, and a prediction unit configured to predict a user activity state after a predetermined time elapses from a current time from the current user activity state recognized by the recognition unit. | 02-03-2011 |
20110110594 | IMAGE PROCESSING SYSTEM, IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM - An image processing system includes a storing section that stores a database in which specific pose data representing each of specific poses of a human, and effect manipulation data specifying each of manipulations applied to an image are registered in association with each other, a human region detecting section that detects a human region that is a region where a human appears in an image on which to perform image processing, a human pose recognizing section that recognizes a pose of the human in the human region detected by the human region detecting section, a matching section that finds the specific pose data matching the pose recognized by the human pose recognizing section, by referencing the database, and a manipulating section that applies a manipulation to the image on the basis of the effect manipulation data associated with the specific pose data found by the matching section. | 05-12-2011 |
20110135192 | LEARNING DEVICE AND METHOD, RECOGNITION DEVICE AND METHOD, AND PROGRAM - A learning device includes: a generating unit configured to generate an image having different resolution from an input image; an extracting unit configured to extract a feature point serving as a processing object from an image generated by the generating unit; a calculating unit configured to calculate the feature amount of the feature point by subjecting the feature point to filter processing employing a predetermined filter; and an identifier generating unit configured to generate an identifier for detecting a predetermined target object from the image by statistical learning employing the feature amount; with the filter including a plurality of regions, and the calculating unit taking the difference value of difference within the regions as the feature amount. | 06-09-2011 |
20110188771 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, AND PROGRAM - An image processing device that recognizes an object present in an image includes a filter calculation unit configured to obtain a plurality of filter outputs by applying a plurality of directional selectivity filters, which respectively correspond to different directions, to the image, and a feature amount calculation unit configured to calculate a plurality of feature amounts with respect to the image based on the filter outputs, which respectively correspond to adjacent angles, of the plurality of directional selectivity filters. | 08-04-2011 |
20110211233 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD AND COMPUTER PROGRAM - An image processing device includes a scanning unit configured to scan a search window on an image to be detected, and a discrimination unit configured to apply one or more rectangle filters for detecting a desired object to an image of the search window at each scan position so as to calculate one or more rectangle features and to discriminate whether or not the object is detected based on the obtained one or more rectangle features. The scanning unit generates integral images corresponding to a size of the search window at every scan position and holds the integral images in a predetermined memory buffer, and the discrimination unit calculates the rectangle features with respect to the image of the search window at each scan position using the integral images held in the memory buffer. | 09-01-2011 |
20110222759 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing apparatus includes a characteristic amount calculating unit calculating a characteristic amount for each of a plurality of n different image patterns, a specifying unit specifying a best-matching image pattern among the plurality of n image patterns for each of frames forming a learning moving picture and having temporal continuity, a computing unit computing a collocation probability Pij indicating a probability that, for a frame located at a position where a temporal distance to a frame for which a first image pattern Xi is specified among the plurality of n image patterns is within a predetermined threshold τ, a second image pattern Xj is specified among the plurality of n image patterns, and a grouping unit grouping the plurality of n image patterns by using the computed collocation probability Pij. | 09-15-2011 |
20110228982 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing device includes a learning image input unit configured to input a learning image, in which a tracked object is captured on different shooting conditions, together with the shooting conditions, a feature response calculation unit configured to calculate a response of one or more integrated features, with respect to the learning image while changing a parameter in accordance with the shooting conditions, a feature learning unit configured to recognize spatial distribution of the one or more integrated features in the learning image based on a calculation result of the response and evaluate a relationship between the shooting conditions and the parameter and a spatial relationship among the integrated features so as to learn a feature of the tracked object, and a feature storage unit configured to store a learning result of the feature. | 09-22-2011 |
20110235926 | INFORMATION PROCESSING APPARATUS, METHOD AND PROGRAM - An information processing apparatus, which creates a tree structure used by a recognition apparatus which recognizes specific information using the tree structure, including a memory unit which stores data including the information to be recognized and data not including the information so as to correspond to a label showing whether or not the data includes the information, a recognition device which recognizes the information and outputs a high score value when the data including the information is input, and a grouping unit which performs grouping of the recognition devices using a score distribution obtained when the data is input into the recognition devices. | 09-29-2011 |
20110239118 | GESTURE INPUT DEVICE, GESTURE INPUT METHOD, AND PROGRAM - There is provided a gesture input device including an input unit to which at least one of image information and voice information representing a user's action is input, a detection unit that detects the user's action based on the input at least one of the image information and the voice information, a prediction unit that predicts one or more gestures that the user desires to input based on a detection result of the action, and a notification unit that notifies the user of an action to be performed next by the user in order to input the predicted one or more gestures. | 09-29-2011 |
20110273592 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, AND PROGRAM - An image processing device includes a clothing extractor extracting a face or head portion from an input image, the face or head portion being a region estimated to be a face or head image, and extracting a clothing region from a region immediately below the face or head portion, the clothing region being a region estimated to be a clothing image, and a clothing converter changing clothing in the input image by performing predetermined image processing on an image in the clothing region in the input image. | 11-10-2011 |
20110299731 | INFORMATION PROCESSING DEVICE AND METHOD, AND PROGRAM - An information processing device includes a first calculation unit which calculates a score of each sample image including a positive image in which an object as an identification object is present and a negative image in which the object as the identification object is not present, for each weak identifier of an identifier including a plurality of weak identifiers, a second calculation unit which calculates the number of scores when the negative image is processed, which are scores less than a minimum score among scores when the positive image is processed; and an realignment unit which realigns the weak identifiers in order from a weak identifier in which the number calculated by the second calculation unit is a maximum. | 12-08-2011 |
20120033861 | SYSTEMS AND METHODS FOR DIGITAL IMAGE ANALYSIS - Systems and methods for implementing a hierarchical image recognition framework for classifying digital images are provided. The provided hierarchical image recognition framework utilizes a multi-layer approach to model training and image classification tasks. A first layer of the hierarchical image recognition framework generates first layer confidence scores, which are utilized by the second layer to produce a final recognition score. The provided hierarchical image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-layer image recognition frameworks. In some embodiments real-time operator guidance is provided for an image classification task. | 02-09-2012 |
20120033862 | SYSTEMS AND METHODS FOR SEGMENTING DIGITAL IMAGES - Methods and systems disclosed herein provide the capability to automatically process digital pathology images quickly and accurately. According to one embodiment, an digital pathology image segmentation task may be divided into at least two parts. An image segmentation task may be carried out utilizing both bottom-up analysis to capture local definition of features and top-down analysis to use global information to eliminate false positives. In some embodiments, an image segmentation task is carried out using a “pseudo-bootstrapping” iterative technique to produce superior segmentation results. In some embodiments, the superior segmentation results produced by the pseudo-bootstrapping method are used as input in a second segmentation task that uses a combination of bottom-up and top-down analysis. | 02-09-2012 |
20120076428 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing device includes: a recognizer configured to recognize a predetermined part of a body of a person from an input image including the person; an evaluator configured to evaluate a difference between a recognized input part and a reference part serving as a basis; and a notifying unit configured to notify information relating to the difference of the input part from the reference part based on an evaluation result. | 03-29-2012 |
20120087556 | DIGITAL IMAGE ANALYSIS USING MULTI-STEP ANALYSIS - Systems and methods for implementing a multi-step image recognition framework for classifying digital images are provided. The provided multi-step image recognition framework utilizes a gradual approach to model training and image classification tasks requiring multi-dimensional ground truths. A first step of the multi-step image recognition framework differentiates a first image region from a remainder image region. Each subsequent step operates on a remainder image region from the previous step. The provided multi-step image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-step image recognition frameworks. | 04-12-2012 |
20120087574 | LEARNING DEVICE, LEARNING METHOD, IDENTIFICATION DEVICE, IDENTIFICATION METHOD, AND PROGRAM - Provided is a learning device including: an acquisition section that acquires a plurality of image pairs in which the same subjects appear and a plurality of image pairs in which different subjects appear; a setting section that sets feature points on one image and the other image of each image pair; a selection section that selects a plurality of prescribed feature points, which are set at the same positions of the one image and the other image, so as to thereby select a feature extraction filter for each prescribed feature point; an extraction section that extracts the features of the prescribed feature points of each of the one image and the other image by using the plurality of feature extraction filters; a calculation section that calculates a correlation between the features; and a learning section that learns a same-subject classifier on the basis of the correlation and label information. | 04-12-2012 |
20120093396 | DIGITAL IMAGE ANALYSIS UTILIZING MULTIPLE HUMAN LABELS - Systems and methods for implementing a multi-label image recognition framework for classifying digital images are provided. The provided multi-label image recognition framework utilizes an iterative, multiple analysis path approach to model training and image classification tasks. A first iteration of the multi-label image recognition framework generates confidence maps for each label, which are shared by the multiple analysis paths to update the confidence maps in subsequent iterations. The provided multi-label image recognition framework permits model training and image classification tasks to be performed more accurately than conventional single-label image recognition frameworks. | 04-19-2012 |
20120128237 | SUPERPIXEL-BOOSTED TOP-DOWN IMAGE RECOGNITION METHODS AND SYSTEMS - Systems and methods for implementing a superpixel boosted top-down image recognition framework are provided. The framework utilizes superpixels comprising contiguous pixel regions sharing similar characteristics. Feature extraction methods described herein provide non-redundant image feature vectors for classification model building. The provided framework differentiates a digitized image into a plurality of superpixels. The digitized image is characterized through image feature extraction methods based on the plurality of superpixels. Image classification models are generated from the extracted image features and ground truth labels and may then be used to classify other digitized images. | 05-24-2012 |
20120250982 | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, AND RECORDING MEDIUM - An image processing apparatus includes: an image feature outputting unit that outputs each of image features in correspondence with a time of the frame; a foreground estimating unit that estimates a foreground image at a time s by executing a view transform as a geometric transform on a foreground view model and outputs an estimated foreground view; a background estimating unit that estimates a background image at the time s by executing a view transform as a geometric transform on a background view model and outputs an estimated background view; a synthesized view generating unit that generates a synthesized view by synthesizing the estimated foreground and background views; a foreground learning unit that learns the foreground view model based on an evaluation value; and a background learning unit that learns the background view model based on the evaluation value by updating the parameter of the foreground view model. | 10-04-2012 |
20120300980 | LEARNING DEVICE, LEARNING METHOD, AND PROGRAM - Disclosed is a learning device. A feature-quantity calculation unit extracts a feature quantity from each feature point of a learning image. An acquisition unit acquires a classifier already obtained by learning as a transfer classifier. A classifier generation unit substitutes feature quantities into weak classifiers constituting the transfer classifier, calculates error rates of the weak classifiers on the basis of classification results of the weak classifiers and a weight of the learning image, and iterates a process of selecting a weak classifier of which the error rate is minimized a plurality of times. In addition, the classifier generation unit generates a classifier for detecting a detection target by linearly coupling a plurality of selected weak classifiers. | 11-29-2012 |
20120306934 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, RECORDING MEDIUM, AND PROGRAM - There is provided an image processing device including a movement section which scrolls a medical image on a screen, and a display control section which, in a case where the medical image is scrolled on the screen, controls a display section to display the medical image in a manner that an observation reference position of a diagnosis region of the medical image passes through a display reference position of a display region of the screen. | 12-06-2012 |
20130142392 | INFORMATION PROCESSING DEVICE AND METHOD, PROGRAM, AND RECORDING MEDIUM - An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation. | 06-06-2013 |
20130182898 | IMAGE PROCESSING DEVICE, METHOD THEREOF, AND PROGRAM - An image processing device includes a difference image generation unit which generates a difference image by obtaining a difference between frames of a cutout image which is obtained by cutting out a predetermined region on a photographed image; a feature amount extracting unit which extracts a feature amount from the difference image; and a recognition unit which recognizes a specific movement of an object on the photographed image based on the feature amount which is obtained from the plurality of difference images which are aligned in time sequence. | 07-18-2013 |
20130243308 | INTEGRATED INTERACTIVE SEGMENTATION WITH SPATIAL CONSTRAINT FOR DIGITAL IMAGE ANALYSIS - An integrated interactive segmentation with spatial constraint method utilizes a combination of several of the most popular online learning algorithms into one and implements a spatial constraint which defines a valid mask local to the user's given marks. Additionally, both supervised learning and statistical analysis are integrated, which are able to compensate each other. Once prediction and activation are obtained, pixel-wised multiplication is conducted to fully indicate how likely each pixel belongs to the foreground or background. | 09-19-2013 |
20150054740 | CLOSE RANGE NATURAL USER INTERFACE SYSTEM AND METHOD OF OPERATION THEREOF - A natural user interface system and method of operation thereof including: a display device having a display screen and a display device camera; a mobile device having a mobile device camera, an optical axis of the mobile device camera positioned at an angle to an optical axis of the display device camera; wherein: the mobile device includes a first device pairing module for pairing the mobile device with the display device; the mobile device camera and the display device camera are for: detecting a user's hand, and determining posture and movement of the user's hand; and the display device includes a motion translation module for translating the posture and movement of the user's hand into a gesture for controlling an element of a user interface on the display screen. | 02-26-2015 |
20150054820 | NATURAL USER INTERFACE SYSTEM WITH CALIBRATION AND METHOD OF OPERATION THEREOF - A natural user interface system and method of operation thereof including: providing a display screen having a range camera connected to the display screen in a known location relative to the display screen; determining a user's pointing vector as pointing towards the display screen; determining the user's pointing vector as motionless; and initializing a cursor in the center of the display screen and simultaneously calibrating the user's pointing vector as an initial pointing vector pointing at the center of the display screen. | 02-26-2015 |