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    • 1. 发明授权
    • Information processing device, information processing method, and program
    • 信息处理装置,信息处理方法和程序
    • US09104980B2
    • 2015-08-11
    • US13429130
    • 2012-03-23
    • Kuniaki NodaTakashi HasuoKenta KawamotoKohtaro Sabe
    • Kuniaki NodaTakashi HasuoKenta KawamotoKohtaro Sabe
    • G06K9/00G06N99/00
    • G06N99/005
    • An information processing device includes a learning unit that performs, using an action performed by an object and an observation value of an image as learning data, learning of a separation learning model that includes a background model that is a model of the background of the image and one or more foreground model(s) that is a model of a foreground of the image, which can move on the background, in which the background model includes a background appearance model indicating the appearance of the background, and at least one among the one or more foreground model(s) includes a transition probability, with which a state corresponding to the position of the foreground on the background is transitioned by an action performed by the object corresponding to the foreground, for each action, and a foreground appearance model indicating the appearance of the foreground.
    • 信息处理装置包括:学习单元,其使用由对象执行的动作和图像的观察值作为学习数据;学习包括作为图像的背景的模型的背景模型的分离学习模型; 以及一个或多个前景模型,其是可以在背景上移动的图像的前景的模型,其中背景模型包括指示背景的外观的背景外观模型,以及至少一个背景模型 一个或多个前景模型包括转移概率,对于每个动作,通过由对应于前景的对象执行的动作来转换对应于背景上的前景的位置的状态,以及前景外观模型 指示前景的外观。
    • 2. 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。
    • 4. 发明授权
    • Image processing system, learning device and method, and program
    • 图像处理系统,学习装置和方法,程序
    • US08582887B2
    • 2013-11-12
    • US11813404
    • 2005-12-26
    • Hirotaka SuzukiAkira NakamuraTakayuki YoshigaharaKohtaro SabeMasahiro Fujita
    • Hirotaka SuzukiAkira NakamuraTakayuki YoshigaharaKohtaro SabeMasahiro Fujita
    • G06K9/00
    • G06K9/00288G06K9/6211G06K9/623G06T7/00
    • The present invention relates to an image processing system, a learning device and method, and a program which enable easy extraction of feature amounts to be used in a recognition process. Feature points are extracted from a learning-use model image, feature amounts are extracted based on the feature points, and the feature amounts are registered in a learning-use model dictionary registration section 23. Similarly, feature points are extracted from a learning-use input image containing a model object contained in the learning-use model image, feature amounts are extracted based on these feature points, and these feature amounts are compared with the feature amounts registered in a learning-use model registration section 23. A feature amount that has formed a pair the greatest number of times as a result of the comparison is registered in the model dictionary registration section 12 as the feature amount to be used in the recognition process. The present invention is applicable to a robot.
    • 本发明涉及图像处理系统,学习装置和方法以及能够容易地提取在识别处理中使用的特征量的程序。 从学习用模型图像提取特征点,基于特征点提取特征量,并且将特征量登记在学习用模型字典注册部23中。同样,从学习用途中提取特征点 基于这些特征点提取含有包含在学习用模型图像中的模型对象的输入图像,并将这些特征量与在学习用模型登记部23中登记的特征量进行比较。特征量 作为比较的结果,在模型字典登记部12中登记了作为识别处理中使用的特征量的最大次数的对。 本发明可应用于机器人。
    • 5. 发明授权
    • Information processing apparatus, information processing method, and program
    • 信息处理装置,信息处理方法和程序
    • US08571315B2
    • 2013-10-29
    • US13288231
    • 2011-11-03
    • Kohtaro SabeKenichi HidaiKiyoto Ichikawa
    • Kohtaro SabeKenichi HidaiKiyoto Ichikawa
    • G06K9/00G06K9/38G06K9/62G06K9/68
    • G06K9/4614G06K9/6256
    • An information processing apparatus includes: a distinguishing unit which, by using an ensemble classifier, which includes a plurality of weak classifiers outputting weak hypotheses which indicates whether a predetermined subject is shown in an image in response to inputs of a plurality of features extracted from the image, and a plurality of features extracted from an input image, sequentially integrates the weak hypotheses output by the weak classifiers in regard to the plurality of features and distinguishes whether the predetermined subject is shown in the input image based on the integrated value. The weak classifier classifies each of the plurality of features to one of three or more sub-divisions based on threshold values, calculates sum divisions of the sub-divisions of the plurality of features as whole divisions into which the plurality of features is classified, and outputs, as the weak hypothesis, a reliability degree of the whole divisions.
    • 一种信息处理装置,包括:识别单元,其使用整体分类器,其包括输出弱假设的多个弱分类器,所述弱分类器指示响应于从所述图像提取的多个特征的输入,是否在图像中示出预定对象 图像和从输入图像提取的多个特征,顺序地对由弱分类器输出的关于多个特征的弱假设进行积分,并且基于积分值区分输入图像中是否显示预定对象。 所述弱分类器基于阈值将所述多个特征中的每一个分类为三个或更多个子分割中的一个,并且将所述多个特征的子分割的和除作为将所述多个特征分类成的整个分割,以及 作为弱假设的输出是整个分区的可靠性程度。
    • 7. 再颁专利
    • Device and method for detecting object and device and method for group learning
    • 用于组学习的物体和装置的检测装置及方法
    • USRE43873E1
    • 2012-12-25
    • US13208123
    • 2011-08-11
    • Kenichi HidaiKohtaro SabeKenta Kawamoto
    • Kenichi HidaiKohtaro SabeKenta Kawamoto
    • G06K9/62G06K9/00
    • G06K9/6282G06K9/00248G06K9/6256
    • An object detecting device for detecting an object in a given gradation image. A scaling section generates scaled images by scaling down a gradation image input from an image output section. A scanning section sequentially manipulates the scaled images and cutting out window images from them and a discriminator judges if each window image is an object or not. The discriminator includes a plurality of weak discriminators that are learned in a group by boosting and an adder for making a weighted majority decision from the outputs of the weak discriminators. Each of the weak discriminators outputs an estimate of the likelihood of a window image to be an object or not by using the difference of the luminance values between two pixels. The discriminator suspends the operation of computing estimates for a window image that is judged to be a non-object, using a threshold value that is learned in advance.
    • 一种用于检测给定灰度图像中的物体的物体检测装置。 缩放部分通过缩小从图像输出部分输入的灰度图像来生成缩放图像。 扫描部分顺序地操纵缩放图像并从中切出窗口图像,并且鉴别器判断每个窗口图像是否是对象。 鉴别器包括通过升压在一组中学习的多个弱识别器和用于从弱识别器的输出进行加权多数决定的加法器。 每个弱识别器通过使用两个像素之间的亮度值的差异来输出窗口图像成为对象的可能性的估计。 鉴别器使用预先学习的阈值暂停对被判断为非对象的窗口图像的计算估计的操作。