Robot apparatus, face recognition method, and face recognition apparatus
    21.
    发明授权
    Robot apparatus, face recognition method, and face recognition apparatus 失效
    机器人装置,人脸识别方法和人脸识别装置

    公开(公告)号:US07369686B2

    公开(公告)日:2008-05-06

    申请号:US10399740

    申请日:2002-08-21

    IPC分类号: G06K9/00

    摘要: 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.

    摘要翻译: 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。

    Operational control method, program, and recording media for robot device, and robot device
    22.
    发明授权
    Operational control method, program, and recording media for robot device, and robot device 失效
    机器人装置的操作控制方法,程序和记录介质,以及机器人装置

    公开(公告)号:US06697711B2

    公开(公告)日:2004-02-24

    申请号:US10258110

    申请日:2002-10-18

    IPC分类号: G06F1900

    CPC分类号: G06N3/008

    摘要: A robot apparatus (1) includes leg blocks (3A to 3D), head block (4), etc. as a moving part (16), a motion controller (102), learning unit (103), prediction unit (104) and a drive unit (105). When the moving part (106), any of the blocks, is operated from outside, the learning unit (103) learns a time-series signal generated due to the external operation. The motion controller (102) and drive unit (105) control together the moving part (106) based on a signal generated at the moving part (106) due to an external force applied to the robot apparatus (1) and a signal having already been learned by the learning unit (103) to make an action taught by the user. The prediction unit (105) predicts whether the moving part (106) makes the taught action according to the initial signal generated at the moving part (106) due to the applied external force. Thus, the robot apparatus (1) can learn an action taught by the user and determine an external force-caused signal to make the taught action.

    摘要翻译: 机器人装置(1)包括作为移动部件(16)的腿部块(3A至3D),头部块(4)等,运动控制器(102),学习单元(103),预测单元(104)和 驱动单元(105)。 当移动部分(106),任何块,从外部操作时,学习单元(103)学习由于外部操作而产生的时间序列信号。 运动控制器(102)和驱动单元(105)基于由于施加到机器人装置(1)的外力而在运动部件(106)处产生的信号,以及已经具有的信号,一起控制运动部件(106) 被学习单元(103)学习以进行用户教导的动作。 预测单元(105)根据施加的外力来预测移动部件(106)是否根据在移动部件(106)产生的初始信号进行教导动作。 因此,机器人装置(1)可以学习用户教导的动作,并确定外力产生的信号以进行教导动作。

    Learning device, learning method, identification device, identification method, and program
    23.
    发明授权
    Learning device, learning method, identification device, identification method, and program 有权
    学习设备,学习方法,识别设备,识别方法和程序

    公开(公告)号:US08811725B2

    公开(公告)日:2014-08-19

    申请号:US13237173

    申请日:2011-09-20

    IPC分类号: G06K9/62

    CPC分类号: G06K9/00288 G06K9/6257

    摘要: 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.

    摘要翻译: 提供一种学习装置,包括:获取部,其获取其中显示相同被摄体的多个图像对以及出现不同主题的多个图像对; 设置部分,其在一个图像上设置特征点,并且每个图像对的另一个图像; 选择部,其选择设置在所述一个图像和所述另一图像的相同位置的多个规定特征点,从而为每个规定的特征点选择特征提取滤波器; 提取部,其使用所述多个特征提取滤波器来提取所述一个图像和所述另一图像中的每一个的规定特征点的特征; 计算部分,其计算特征之间的相关性; 以及基于相关性和标签信息学习相同主题分类器的学习部分。

    Gesture input device, gesture input method, and program
    24.
    发明授权
    Gesture input device, gesture input method, and program 有权
    手势输入设备,手势输入法和程序

    公开(公告)号:US08726196B2

    公开(公告)日:2014-05-13

    申请号:US13045777

    申请日:2011-03-11

    CPC分类号: G06F3/017 G10L15/02

    摘要: A gesture input device includes an input unit to which image information representing an action is input. The gesture input device also includes a detection unit that detects the action based on a shape of the input image information. The gesture input device further includes a prediction unit that predicts one or more gestures based on a detection result of the action. In addition, the gesture input device includes a notification unit that notifies an action to be performed next to input the predicted one or more gestures.

    摘要翻译: 手势输入装置包括输入表示动作的图像信息的输入单元。 手势输入装置还包括基于输入图像信息的形状来检测动作的检测单元。 手势输入装置还包括:预测单元,其基于动作的检测结果预测一个或多个手势。 此外,手势输入装置包括通知单元,其通知下一步要执行的动作来输入预测的一个或多个手势。

    Information processing apparatus, method and program
    25.
    发明授权
    Information processing apparatus, method and program 有权
    信息处理装置,方法和程序

    公开(公告)号:US08606022B2

    公开(公告)日:2013-12-10

    申请号:US13038908

    申请日:2011-03-02

    申请人: Jun Yokono

    发明人: Jun Yokono

    IPC分类号: G06K9/62

    摘要: 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.

    摘要翻译: 一种信息处理装置,其创建由识别装置使用的树结构,所述树结构使用所述树结构识别特定信息,所述信息处理装置包括存储单元,所述存储单元存储包括要被识别的信息的数据和不包括所述信息的数据,以便对应于标签 显示数据是否包括该信息;识别装置,其识别该信息并在输入包括该信息的数据时输出高分值;以及分组单元,其使用当该 数据被输入到识别装置中。

    Superpixel-boosted top-down image recognition methods and systems
    26.
    发明授权
    Superpixel-boosted top-down image recognition methods and systems 有权
    超像素增强自顶向下图像识别方法和系统

    公开(公告)号:US08588518B2

    公开(公告)日:2013-11-19

    申请号:US12951702

    申请日:2010-11-22

    IPC分类号: G06K9/62

    摘要: 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.

    摘要翻译: 提供了用于实现超像素增强自顶向下图像识别框架的系统和方法。 框架利用包含具有相似特征的相邻像素区域的超像素。 本文描述的特征提取方法提供用于分类模型构建的非冗余图像特征向量。 所提供的框架将数字化图像区分为多个超像素。 数字化图像的特征在于基于多个超像素的图像特征提取方法。 图像分类模型从提取的图像特征和地面真值标签生成,然后可以用于对其他数字化图像进行分类。

    Device, method, and computer-readable storage medium for compositing images
    27.
    发明授权
    Device, method, and computer-readable storage medium for compositing images 有权
    用于合成图像的设备,方法和计算机可读存储介质

    公开(公告)号:US08582806B2

    公开(公告)日:2013-11-12

    申请号:US12571923

    申请日:2009-10-01

    IPC分类号: G06K9/00

    CPC分类号: G06K9/00369 G06K9/4619

    摘要: 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.

    摘要翻译: 图像处理装置包括检测器,设置单元和图像生成器。 检测器从第一图像检测目标对象图像区域。 当一个或多个预定参数可应用于由检测器检测到的区域内的目标对象时,设置单元将相关目标对象图像区域设置为第一区域。 然后,图像生成器通过对第一区域内的图像部分或者包含第一区域中不包含第一图像内的图像部分的第二区域中的图像部分施加预定处理来生成第二图像。

    Learning-based feature detection processing device and method
    28.
    发明授权
    Learning-based feature detection processing device and method 有权
    基于学习的特征检测处理装置及方法

    公开(公告)号:US08494258B2

    公开(公告)日:2013-07-23

    申请号:US12571946

    申请日:2009-10-01

    IPC分类号: G06K9/00 G06K9/46 G06K9/62

    摘要: 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.

    摘要翻译: 学习装置包括图像生成器,特征点提取器,特征量计算器和分类器生成器。 图像发生器从输入图像生成具有不同比例系数的图像。 特征点提取器从图像生成器生成的每个图像中提取特征点。 特征值计算器通过使用预定滤波器对特征点进行滤波来计算特征点的特征值。 分类器生成器通过使用特征值的统计学习来生成用于从图像检测预定目标对象的一个​​或多个分类器。

    Digital image analysis utilizing multiple human labels
    29.
    发明授权
    Digital image analysis utilizing multiple human labels 有权
    使用多个人体标签的数字图像分析

    公开(公告)号:US08379994B2

    公开(公告)日:2013-02-19

    申请号:US12904138

    申请日:2010-10-13

    IPC分类号: G06K9/62

    CPC分类号: G06K9/6262 G06K9/6232

    摘要: 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.

    摘要翻译: 提供了用于实现用于分类数字图像的多标签图像识别框架的系统和方法。 提供的多标签图像识别框架利用迭代的多分析路径方法来对训练和图像分类任务进行建模。 多标签图像识别框架的第一迭代生成每个标签的置信图,其由多个分析路径共享以在后续迭代中更新置信度图。 提供的多标签图像识别框架允许模型训练和图像分类任务比传统的单标签图像识别框架更准确地执行。

    IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, AND RECORDING MEDIUM
    30.
    发明申请
    IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, AND RECORDING MEDIUM 有权
    图像处理设备,图像处理方法,程序和记录介质

    公开(公告)号:US20120250982A1

    公开(公告)日:2012-10-04

    申请号:US13427199

    申请日:2012-03-22

    IPC分类号: G06K9/62

    摘要: 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.

    摘要翻译: 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。