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21. 发明授权

US07801354B2 Image processing system 失效
标题翻译：图像处理系统
公开(公告)号：US07801354B2
公开(公告)日：2010-09-21
申请号：US11589872
申请日：2006-10-31
申请人： Jun Yokono
发明人： Jun Yokono
IPC分类号： G06K9/62
CPC分类号： G06K9/6228 , G06K9/6211 , G06K9/6256
摘要： An image processing system includes a learning device generating, in advance, a recognizer for recognizing a recognition target; and a recognition device recognizing, using the recognizer, whether a recognition image includes the recognition target. The learning device includes model feature point generator for generating model feature points, model feature quantity generator for generating model-feature quantities, learning feature point generator for generating learning feature points, learning feature quantity generator for generating learning feature quantities, learning correlation feature quantity generator for generating a learning correlation feature quantity, and recognizer generator for generating the recognizer. The recognition device includes recognition feature point generator for generating recognition feature points, recognition feature quantity generator for generating recognition feature quantities, recognition correlation feature quantity generator for generating a recognition correlation feature quantity, and recognition processor for determining whether the recognition image includes the recognition target.
摘要翻译：图像处理系统包括学习装置，预先生成用于识别识别对象的识别器; 以及识别装置，使用所述识别器识别识别图像是否包括所述识别对象。学习装置包括用于生成模型特征点的模型特征点生成器，用于生成模型特征量的模型特征量生成器，用于生成学习特征点的学习特征点生成器，用于生成学习特征量的学习特征量生成器，学习相关特征量生成器用于生成学习相关特征量，以及用于生成识别器的识别器发生器。识别装置包括用于产生识别特征点的识别特征点发生器，用于产生识别特征量的识别特征量发生器，用于产生识别相关特征量的识别相关特征量发生器和用于确定识别图像是否包括识别目标的识别处理器。

22. 发明申请

US20100188519A1 Information Processing Device and Method, Program, and Recording Medium 有权
标题翻译：信息处理设备和方法，程序和记录介质
公开(公告)号：US20100188519A1
公开(公告)日：2010-07-29
申请号：US12688665
申请日：2010-01-15
申请人： Keisuke YAMAOKA , Jun Yokono
发明人： Keisuke YAMAOKA , Jun Yokono
IPC分类号： H04N5/228 , G06K9/46
CPC分类号： G06F3/017 , A63F13/40 , G06F3/005 , G06F3/011 , G06F3/0304 , G06K9/00342 , G06K9/00369 , H04N5/222 , H04N5/2224
摘要： An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation.
摘要翻译：一种信息处理装置，包括：轮廓提取单元，从被摄体的拍摄图像中提取被检体的轮廓; 特征量提取单元，对于每个采样点，通过从构成轮廓的点提取采样点来提取特征量; 估计单元，通过计算在特征量提取单元中提取的特征量的程度与预先准备的表示的多个特征量中的每一个相匹配来估计高度匹配的姿势作为对象的姿势预定姿势彼此不同; 以及确定单元，当估计单元执行估计时，使用匹配成本确定估计单元的估计精度。

23. 发明授权

US07369686B2 Robot apparatus, face recognition method, and face recognition apparatus 失效
标题翻译：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
申请人： Jun Yokono , Kohtaro Sabe , Kenta Kawamoto
发明人： Jun Yokono , Kohtaro Sabe , Kenta Kawamoto
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/00221 , G06K9/00228
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。

24. 发明授权

US08811725B2 Learning device, learning method, identification device, identification method, and program 有权
标题翻译：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
申请人： Jun Yokono , Atsushi Okubo
发明人： Jun Yokono , Atsushi Okubo
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。

25. 发明授权

US08726196B2 Gesture input device, gesture input method, and program 有权
标题翻译：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
申请人： Keisuke Yamaoka , Jun Yokono , Yuichi Hasegawa , Ning Zhou , Hirotaka Suzuki
发明人： Keisuke Yamaoka , Jun Yokono , Yuichi Hasegawa , Ning Zhou , Hirotaka Suzuki
IPC分类号： G06F3/033 , G06K9/00 , G06K3/00 , G06F3/01
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。

26. 发明授权

US08606022B2 Information processing apparatus, method and program 有权
标题翻译：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
CPC分类号： G06K9/6224 , G06K9/00375 , G06K9/6282
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。

27. 发明授权

US08588518B2 Superpixel-boosted top-down image recognition methods and systems 有权
标题翻译：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
申请人： Su Wang , Shengyang Dai , Akira Nakamura , Takeshi Ohashi , Jun Yokono
发明人： Su Wang , Shengyang Dai , Akira Nakamura , Takeshi Ohashi , Jun Yokono
IPC分类号： G06K9/62
CPC分类号： G06K9/4671 , G06K9/468 , G06T7/12 , G06T2207/20076
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。

28. 发明授权

US08582806B2 Device, method, and computer-readable storage medium for compositing images 有权
标题翻译：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
申请人： Jun Yokono , Yuichi Hasegawa
发明人： Jun Yokono , Yuichi Hasegawa
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。

29. 发明授权

US08494258B2 Learning-based feature detection processing device and method 有权
标题翻译：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
申请人： Jun Yokono , Yuichi Hasegawa
发明人： Jun Yokono , Yuichi Hasegawa
IPC分类号： G06K9/00 , G06K9/46 , G06K9/62
CPC分类号： G06K9/00369 , G06K9/00375 , G06K9/4609 , G06K9/4619 , G06K9/6256
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。

30. 发明授权

US08379994B2 Digital image analysis utilizing multiple human labels 有权
标题翻译：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
申请人： Shengyang Dai , Su Wang , Akira Nakamura , Takeshi Ohashi , Jun Yokono
发明人： Shengyang Dai , Su Wang , Akira Nakamura , Takeshi Ohashi , Jun Yokono
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。

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