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    • 1. 发明授权
    • Apparatus, method, and program for predicting user activity state through data processing
    • 用于通过数据处理预测用户活动状态的装置,方法和程序
    • US08560467B2
    • 2013-10-15
    • US12839321
    • 2010-07-19
    • Masato ItoKohtaro SabeHirotaka SuzukiJun YokonoKazumi AoyamaTakashi Hasuo
    • Masato ItoKohtaro SabeHirotaka SuzukiJun YokonoKazumi AoyamaTakashi Hasuo
    • G06F15/18
    • G06K9/00335G06K9/00664G06K9/00778
    • A data processing apparatus includes an obtaining unit for obtaining time-series data, an activity model learning unit for learning an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit for recognizing a current user activity state by using the learned activity model, and a prediction unit for predicting a user activity state after a predetermined time elapses from a current time from the recognized current user activity state, wherein the prediction unit predicts the user activity state as an occurrence probability, and calculates the occurrence probabilities of the respective states on the basis of the state transition probability of the stochastic state transition model to predict the user activity state, while it is presumed that observation probabilities of the respective states at the respective times of the stochastic state transition model are an equal probability.
    • 数据处理装置包括:获取单元,用于获取时间序列数据;活动模型学习单元,用于从所获得的时间序列数据中学习表示用户活动状态的活动模型作为随机状态转换模型;识别单元,用于识别 通过使用所学习的活动模型的当前用户活动状态,以及预测单元,用于在从所识别的当前用户活动状态起从当前时间经过预定时间之后预测用户活动状态,其中,所述预测单元将所述用户活动状态预测为发生 概率,并且基于随机状态转换模型的状态转移概率来计算各个状态的发生概率以预测用户活动状态,同时假设在随机的各个时间的各个状态的观察概率 状态转换模型是相等的概率。
    • 5. 发明申请
    • IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, AND RECORDING MEDIUM
    • 图像处理设备,图像处理方法,程序和记录介质
    • US20120250982A1
    • 2012-10-04
    • US13427199
    • 2012-03-22
    • Masato ITOKohtaro SabeJun Yokono
    • Masato ITOKohtaro SabeJun Yokono
    • G06K9/62
    • G06T7/0042G06T7/12G06T7/174G06T7/194G06T7/73G06T2207/20081G06T2207/20164
    • 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.
    • 一种图像处理装置包括:图像特征输出单元,其与帧的时间相对应地输出每个图像特征; 前景估计单元,其通过在前景视图模型上执行视角变换作为几何变换来估计时间s的前景图像,并输出估计的前景视图; 背景估计单元,其通过在背景视图模型上执行视图变换作为几何变换来估计在时间s的背景图像,并输出估计的背景视图; 合成视图生成单元,其通过合成估计的前景和背景视图来生成合成视图; 前景学习单元,其基于评估值学习前景视图模型; 以及背景学习单元,通过更新前景视图模型的参数,基于评估值来学习背景视图模型。
    • 6. 发明授权
    • Image processing apparatus, image processing method, program, and recording medium for learning from moving images
    • 图像处理装置,图像处理方法,程序和用于从运动图像学习的记录介质
    • US08849017B2
    • 2014-09-30
    • US13427199
    • 2012-03-22
    • Masato ItoKohtaro SabeJun Yokono
    • Masato ItoKohtaro SabeJun Yokono
    • G06K9/62G06T7/00
    • G06T7/0042G06T7/12G06T7/174G06T7/194G06T7/73G06T2207/20081G06T2207/20164
    • 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.
    • 一种图像处理装置包括:图像特征输出单元,其与帧的时间相对应地输出每个图像特征; 前景估计单元,其通过在前景视图模型上执行视角变换作为几何变换来估计时间s的前景图像,并输出估计的前景视图; 背景估计单元,其通过在背景视图模型上执行视图变换作为几何变换来估计在时间s的背景图像,并输出估计的背景视图; 合成视图生成单元,其通过合成估计的前景和背景视图来生成合成视图; 前景学习单元,其基于评估值学习前景视图模型; 以及背景学习单元,通过更新前景视图模型的参数,基于评估值来学习背景视图模型。
    • 7. 发明申请
    • FACE IMAGE PROCESSING APPARATUS, FACE IMAGE PROCESSING METHOD, AND COMPUTER PROGRAM
    • 面部图像处理设备,脸部图像处理方法和计算机程序
    • US20090060290A1
    • 2009-03-05
    • 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。
    • 8. 发明授权
    • Information processing device and method, and program
    • 信息处理装置及方法,程序
    • US08755594B2
    • 2014-06-17
    • 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。
    • 9. 发明申请
    • Image Processing Apparatus, Image Processing Method, and Program
    • 图像处理装置,图像处理方法和程序
    • US20070242876A1
    • 2007-10-18
    • US11697203
    • 2007-04-05
    • Kohtaro SabeJun Yokono
    • Kohtaro SabeJun Yokono
    • G06K9/00
    • G06K9/4652G06K9/6203G06K2009/6213
    • The present invention provides an image processing apparatus to recognize a predetermined model whose surface has a plurality of colors from an input color image that is obtained by capturing an image of a color object whose surface has a plurality of colors. The image processing apparatus includes a detecting unit configured to detect color areas from the input color image, each color area including adjoining pixels of the same color; and a recognizing unit configured to determine whether the color areas on the input color image detected by the detecting unit correspond to parts of the model to which color areas on a reference color image obtained by capturing an image of the model correspond, and determine whether the color object in the input color image is the model on the basis of the determination result.
    • 本发明提供了一种图像处理装置,其从通过捕获其表面具有多种颜色的彩色对象的图像而获得的输入彩色图像来识别其表面具有多种颜色的预定模型。 所述图像处理装置包括检测单元,其被配置为从所述输入彩色图像检测颜色区域,每个颜色区域包括相同颜色的相邻像素; 以及识别单元,其被配置为确定由所述检测单元检测到的输入彩色图像上的颜色区域是否对应于通过捕获所述模型的图像而获得的参考彩色图像上的颜色区域对应的模型的部分,并且确定是否 输入彩色图像中的彩色对象是基于确定结果的模型。
    • 10. 发明授权
    • Robot apparatus, face recognition method, and face recognition apparatus
    • 机器人装置,人脸识别方法和人脸识别装置
    • US07369686B2
    • 2008-05-06
    • US10399740
    • 2002-08-21
    • Jun YokonoKohtaro SabeKenta Kawamoto
    • Jun YokonoKohtaro SabeKenta Kawamoto
    • G06K9/00
    • G06K9/00288G06K9/00221G06K9/00228
    • A robot includes a face extracting section for extracting features of a face included in an image captured by a CCD camera, and a face recognition section for recognizing the face based on a result of face extraction by the face extracting section. The face extracting section is implemented by Gabor filters that filter images using a plurality of filters that have orientation selectivity and that are associated with different frequency components. The face recognition section is implemented by a support vector machine that maps the result of face recognition to a non-linear space and that obtains a hyperplane that separates in that space to discriminate a face from a non-face. The robot is allowed to recognize a face of a user within a predetermined time under a dynamically changing environment.
    • 机器人包括:面部提取部,用于提取由CCD照相机拍摄的图像中包含的面部的特征;以及面部识别部,其基于面部提取部的面部提取的结果识别脸部。 人脸提取部分由Gabor滤波器实现,该滤波器使用具有取向选择性并且与不同频率分量相关联的多个滤波器对图像进行滤波。 脸部识别部分由支持向量机实现,该支持向量机将人脸识别的结果映射到非线性空间,并获得在该空间中分离的超平面,以将脸部与非脸部区分开。 允许机器人在动态变化的环境下在预定时间内识别用户的脸部。