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    • 43. 发明授权
    • Obstacle recognition apparatus and method, obstacle recognition program, and mobile robot apparatus
    • 障碍识别装置和方法,障碍物识别程序和移动机器人装置
    • US07386163B2
    • 2008-06-10
    • US10387647
    • 2003-03-13
    • Kohtaro SabeKenta KawamotoTakeshi OhashiMasaki FukuchiAtsushi OkuboSteffen Gutmann
    • Kohtaro SabeKenta KawamotoTakeshi OhashiMasaki FukuchiAtsushi OkuboSteffen Gutmann
    • G06K9/00H04N15/00H04N7/00H04N7/18G06F19/00G06F17/10G01C22/00
    • G06K9/00664G06T7/97
    • An obstacle recognition apparatus is provided which can recognize an obstacle by accurately extracting a floor surface. It includes a distance image generator (222) to produce a distance image using a disparity image and homogeneous transform matrix, a plane detector (223) to detect plane parameters on the basis of the distance image from the distance image generator (222), a coordinate transformer (224) to transform the homogeneous transform matrix into a coordinate of a ground-contact plane of a robot apparatus (1), and a floor surface detector (225) to detect a floor surface using the plane parameters from the plane detector (223) and result of coordinate transformation from the coordinate transformer (224) and supply the plane parameters to an obstacle recognition block (226). The obstacle recognition block (226) selects one of points on the floor surface using the plane parameters of the floor surface detected by the floor surface detector (225) and recognizes an obstacle on the basis of the selected point.
    • 提供了能够通过精确地提取地板面来识别障碍物的障碍物识别装置。 它包括使用视差图像和均匀变换矩阵产生距离图像的距离图像生成器(222),基于距离图像生成器(222)的距离图像检测平面参数的平面检测器(223), 将所述均匀变换矩阵变换为机器人装置(1)的接地面的坐标的坐标变换器(224)和使用来自所述平面检测器的平面参数来检测地板面的地板面检测器(225) 223)和从坐标变换器(224)的坐标变换的结果,并将平面参数提供给障碍物识别块(226)。 障碍物识别块(226)使用由地板表面检测器(225)检测到的地板表面的平面参数来选择地板表面上的一个点,并基于所选择的点识别障碍物。
    • 44. 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。
    • 45. 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。
    • 47. 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。