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    • 51. 发明授权
    • Learning device and method, recognition device and method, and program
    • 学习装置与方法,识别装置及方法及程序
    • US09275305B2
    • 2016-03-01
    • US12915838
    • 2010-10-29
    • Jun Yokono
    • Jun Yokono
    • G06K9/00G06K9/62G06K9/46
    • G06K9/6256G06K9/00369G06K9/46G06K9/4614G06K9/4619G06K9/4642G06K9/4647G06K9/468G06K2009/4666
    • 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.
    • 学习装置包括:生成单元,被配置为从输入图像生成具有不同分辨率的图像; 提取单元,被配置为从由所述生成单元生成的图像提取用作处理对象的特征点; 计算单元,被配置为通过对特征点进行使用预定滤波器的滤波处理来计算特征点的特征量; 以及标识符生成单元,被配置为通过使用所述特征量的统计学习从所述图像生成用于检测预定目标对象的标识符; 所述滤波器包括多个区域,并且所述计算单元将所述区域内的差值的差值作为特征量。
    • 52. 发明授权
    • Systems and methods for digital image analysis
    • 数字图像分析的系统和方法
    • US09208405B2
    • 2015-12-08
    • US12851818
    • 2010-08-06
    • Shengyang DaiSu WangAkira NakamuraTakeshi OhashiJun Yokono
    • Shengyang DaiSu WangAkira NakamuraTakeshi OhashiJun Yokono
    • G06K9/00G06K9/62
    • G06K9/6292G06K9/6254
    • 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.
    • 提供了用于实现用于分类数字图像的分层图像识别框架的系统和方法。 所提供的分层图像识别框架利用多层方法对训练和图像分类任务进行建模。 分层图像识别框架的第一层产生第一层置信度得分,其由第二层利用以产生最终识别分数。 所提供的分层图像识别框架允许模型训练和图像分类任务以比常规单层图像识别框架更精确和更少资源密集的方式执行。 在一些实施例中,为图像分类任务提供了实时操作者指导。
    • 55. 发明授权
    • Face image processing apparatus, face image processing method, and computer program
    • 面部图像处理装置,面部图像处理方法和计算机程序
    • US08331616B2
    • 2012-12-11
    • US12191610
    • 2008-08-14
    • Kohtaro SabeAtsushi OkuboJun Yokono
    • Kohtaro SabeAtsushi OkuboJun Yokono
    • G06K9/00
    • G06K9/00248
    • 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.
    • 面部图像处理装置通过统计学习选择特征点和特征来识别人。 该装置包括用于输入由任意面部检测装置检测到的面部图像的输入装置,用于从输入面部图像检测几个位置中的面部部分的位置的面部部位检测装置,基于检测位置估计面部姿势的面部姿势估计装置 特征点位置校正装置,用于根据面部姿势估计装置的面部姿势的估计结果校正用于识别人的每个特征点的位置,以及面部识别装置,用于通过计算特征来识别人物 通过特征点位置校正装置执行位置校正之后的每个特征点处的输入面部图像,并针对登记面部的特征检查特征。
    • 57. 发明申请
    • SYSTEMS AND METHODS FOR DIGITAL IMAGE ANALYSIS
    • 数字图像分析系统与方法
    • US20120033861A1
    • 2012-02-09
    • US12851818
    • 2010-08-06
    • Shengyang DaiSu WangAkira NakamuraTakeshi OhashiJun Yokono
    • Shengyang DaiSu WangAkira NakamuraTakeshi OhashiJun Yokono
    • G06K9/00
    • G06K9/6292G06K9/6254
    • 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.
    • 提供了用于实现用于分类数字图像的分层图像识别框架的系统和方法。 所提供的分层图像识别框架利用多层方法对训练和图像分类任务进行建模。 分层图像识别框架的第一层产生第一层置信度得分,其由第二层利用以产生最终识别分数。 所提供的分层图像识别框架允许模型训练和图像分类任务以比常规单层图像识别框架更精确和更少资源密集的方式执行。 在一些实施例中,为图像分类任务提供了实时操作者指导。
    • 58. 发明申请
    • INFORMATION PROCESSING DEVICE AND METHOD, AND PROGRAM
    • 信息处理设备和方法,程序
    • US20110299731A1
    • 2011-12-08
    • US13116412
    • 2011-05-26
    • Jun YokonoKohtaro Sabe
    • Jun YokonoKohtaro Sabe
    • G06K9/00
    • G06K9/6257G06K9/00791G06K2009/4666
    • 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.
    • 一种信息处理设备,包括:第一计算单元,其计算包含其中存在作为识别对象的对象的正图像和不存在作为识别对象的对象的负图像的每个样本图像的得分,对于每个弱 标识符包括多个弱标识符的标识符;第二计算单元,当处理正图像时,计算负图像处理时的得分数,该分数小于分数中的最小得分; 以及重新排列单元,其从由第二计算单元计算的数量最大的弱识别符依次重新排列弱标识符。