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    • 2. 发明授权
    • Motor
    • 发动机
    • US08816554B2
    • 2014-08-26
    • US13574531
    • 2011-03-07
    • Hu LiYuichi YoshikawaHiroshi MurakamiHideaki MatsuoYuichiro Tashiro
    • Hu LiYuichi YoshikawaHiroshi MurakamiHideaki MatsuoYuichiro Tashiro
    • H02K16/00
    • H02K21/029
    • A clutch mechanism moving together with an actuator allows coupling or decoupling an inner rotor to or from a power shaft, thereby controlling a rotation angle. This structure allows a polarity of a magnetic pole of the inner rotor to be the same as that of an opposing magnetic pole of an outer rotor when the motor is driven at a low rpm, so that magnetic fluxes inter-linking with windings can be increased, which results in greater torque. When the motor is driven at a high rpm, the structure allows the polarity of the magnetic pole of the inner rotor to be different from that of the opposing magnetic pole of the outer rotor, so that an amount of leakage flux is increased, and the magnetic fluxes inter-linking with the winding are decreased. As a result, an induction voltage is lowered and a high rpm range is widened.
    • 与致动器一起移动的离合器机构允许将内转子与动力轴联接或解耦,由此控制旋转角度。 当电动机以低转速驱动时,该结构允许内转子的磁极的极性与外转子的相对磁极的极性相同,使得可以增加与绕组相互联系的磁通量 ,这导致更大的扭矩。 当电动机以高转速驱动时,该结构允许内转子的磁极的极性与外转子的相对磁极的极性不同,使得漏磁通量增加, 与绕组相互连接的磁通量减少。 结果,感应电压降低,高转速范围变宽。
    • 3. 发明授权
    • Videophone terminal
    • 视频电话终端
    • US07202886B2
    • 2007-04-10
    • US10803239
    • 2004-03-18
    • Hideaki MatsuoTakahiro MakinoFumihiko YamadaMakoto NishimuraTetsu Hada
    • Hideaki MatsuoTakahiro MakinoFumihiko YamadaMakoto NishimuraTetsu Hada
    • H04N7/14
    • G06T13/80
    • The present invention provides a videophone terminal by which the emotions and impressions of a user can be transmitted to and easily understood by a co-communicant. When a user performs a predetermined operation or when an audio processor identifies a predetermined keyword in the speech of the user, a picture of a virtual character is modified, or a completely different picture is displayed. To modify the picture of the virtual character, the size of each part of the face or the whole face is changed, or a pattern expressing an emotion is added thereto. And when a pending mode is released, the virtual character is recovered and displayed on the screen while a melody is played. At the end of a video conversation, in accordance with the user's selection, a picture indicating that the virtual character disappears from the screen is displayed before disconnecting the line.
    • 本发明提供了一种可视电话终端,通过该视频电话终端可以将用户的情感和印象传送给共同通信者并且易于理解。 当用户执行预定操作时,或者当音频处理器识别用户的语音中的预定关键字时,修改虚拟角色的图片,或者显示完全不同的图片。 为了修改虚拟角色的图片,改变脸部或整个面部的每个部分的大小,或者添加表达情绪的图案。 而当待机模式被释放时,虚拟角色被恢复并显示在屏幕上,同时播放旋律。 在视频会话结束时,根据用户的选择,在断开线路之前,显示指示虚拟角色从屏幕消失的图片。
    • 4. 发明授权
    • Hand gesture recognizing device
    • 手势识别装置
    • US06215890B1
    • 2001-04-10
    • US09160048
    • 1998-09-25
    • Hideaki MatsuoYuji TakataTerutaka TeshimaSeiji IgiShan LuKazuyuki Imagawa
    • Hideaki MatsuoYuji TakataTerutaka TeshimaSeiji IgiShan LuKazuyuki Imagawa
    • G06F936
    • G06F3/017G06K9/00355H04N13/239H04N13/243H04N2013/0081
    • A hand gesture recognizing device is provided which can correctly recognize hand gestures at high speed without requiring users to be equipped with tools. A gesture of a user is stereoscopically filmed by a photographing device 1 and then stored in an image storage device 2. A feature image extracting device 3 transforms colors of the stereoscopic image data read from the image storage device 2 in accordance with color transformation tables created by a color transformation table creating device 13, and disassembles and outputs the feature image of the user in corresponding channels. A spatial position calculating device 4 calculates spatial positions of feature parts of the user by utilizing parallax of the feature image outputted from the feature image extracting device 4. A region dividing device 5 defines the space around the user with spatial region codes. A hand gesture detecting device 6 detects how the hands of the user move in relation to the spatial region codes. A category is detected first on the basis of the detected hand gesture, and then a sign language word in that category is specified.
    • 提供了一种手势识别装置,其可以在不需要用户配备工具的情况下以高速度正确识别手势。 用户的手势由拍摄装置1立体地拍摄,然后存储在图像存储装置2中。特征图像提取装置3根据所生成的颜色变换表,转换从图像存储装置2读取的立体图像数据的颜色 通过颜色变换表创建装置13,并且在对应的频道中分解并输出用户的特征图像。 空间位置计算装置4通过利用从特征图像提取装置4输出的特征图像的视差来计算用户的特征部分的空间位置。区域划分装置5使用空间区域码定义用户周围的空间。 手势检测装置6检测用户的手相对于空间区域代码移动的方式。 首先基于检测到的手势来检测类别,然后指定该类别中的手语。
    • 7. 发明授权
    • Image processing method and apparatus for comparing edges between images
    • 用于比较图像之间的边缘的图像处理方法和装置
    • US07227996B2
    • 2007-06-05
    • US10057756
    • 2002-01-25
    • Kazuyuki ImagawaTetsuya YoshimuraKatsuhiro IwasaHideaki MatsuoYuji Takata
    • Kazuyuki ImagawaTetsuya YoshimuraKatsuhiro IwasaHideaki MatsuoYuji Takata
    • G06K9/00G06K9/46G06K9/62G06K9/66
    • G06K9/6202G06K9/522
    • An image processing method for detecting an object from an input image using a template image, including inputting a specified image with respect to both a template image and an input image, calculating an edge normal direction vector of said specified image, generating an evaluation vector from said edge normal direction vector, subjecting the evaluation vector to orthogonal transformation, a step of performing a product sum calculation of corresponding spectral data with respect to each evaluation vector that has been subjected to orthogonal transformation and has been obtained for each of said template image and said input image, and a step of subjecting it to inverse orthogonal transformation and generating a similarity value map. The formula of the similarity value, the orthogonal transformation, and the inverse orthogonal transformation each have linearity. The pattern recognition is one in which the component of the similarity value is not subjected to positive/negative reversal through variations in brightness of the background.
    • 一种用于使用模板图像从输入图像中检测对象的图像处理方法,包括相对于模板图像和输入图像输入指定图像,计算所述指定图像的边缘法线方向向量,从 所述边缘法线方向矢量,对所述评估矢量进行正交变换,对相对于已进行了正交变换的评估矢量对应的光谱数据进行乘积和计算的步骤,并且对于所述模板图像和 所述输入图像,以及对其进行逆正交变换并产生相似度值图的步骤。 相似度公式,正交变换和逆正交变换各具有线性关系。 模式识别是通过背景亮度的变化,相似度值的分量不经受正/负反转的模式识别。
    • 9. 发明授权
    • Device and method for recognizing hand shape and position, and recording medium having program for carrying out the method recorded thereon
    • 用于识别手形和位置的装置和方法,以及具有用于执行记录在其上的方法的程序的记录介质
    • US06819782B1
    • 2004-11-16
    • US09588948
    • 2000-06-08
    • Kazuyuki ImagawaHideaki MatsuoSeiji IgiShan Lu
    • Kazuyuki ImagawaHideaki MatsuoSeiji IgiShan Lu
    • G06K900
    • G06K9/00375G06K9/00355G06T7/74
    • An object of the present invention is to provide a device and a method for recognizing hand shape and position even if a hand image to be provided for recognition is rather complicated in shape, and a recording medium having a program for carrying out the method recorded thereon. A hand image normalization part 11 deletes a wrist region respectively from a plurality of images varied in hand shape and position before subjecting the images to normalization in hand orientation and size to generate hand shape images. An eigenspace calculation part 13 calculates an eigenvalue and an eigenvector respectively from the hand shape images under an analysis based on an eigenspace method. An eigenspace projection part 15 calculates eigenspace projection coordinates by projecting the hand shape images onto an eigenspace having the eigenvectors as a basis. A hand image normalization part 21 deletes a wrist region from an input hand image, and generates an input hand shape image by normalizing the input hand image to be equivalent to the hand shape images. An eigenspace projection part 22 calculates eigenspace projection coordinates for the input hand shape image by projecting the same onto the eigenspace having the eigenvectors as the basis. A hand shape image selection part 23 compares the eigenspace projection coordinates calculated for the input hand shape image with each of the eigenspace projection coordinates calculated for the hand shape images, and then determines which of the hand shape images is closest to the input hand shape image. A shape/position output part 24 outputs shape information and position information on the determined hand shape image.
    • 本发明的目的是提供一种用于识别手形和位置的装置和方法,即使要提供用于识别的手形图像的形状相当复杂,并且具有用于执行其上记录的方法的程序的记录介质 手图像归一化部11分别从手形和位置变化的多个图像中分离手腕区域,然后使图像在手方向和尺寸上进行归一化以产生手形图像。 本征空间计算部13基于本征空间法在分析下从手形图像分别计算特征值和特征向量。 本征空间投影部15通过将手形图像投影到具有特征向量的本征空间作为基础来计算本征空间投影坐标。 手形图像归一化部21从输入的手图像中删除腕部区域,并且通过将输入的手图像归一化为与手形图像相当的手段来生成输入的手形图像。 本征空间投影部22通过将其投影到具有特征向量的本征空间作为基础,来计算输入的手形图像的本征空间投影坐标。 手形图像选择部23将输入的手形图像计算出的本征空间投影坐标与针对手形图像计算的每个本征空间投影坐标进行比较,然后确定手形图像中哪一个最接近输入的手形图像 。 形状/位置输出部24输出关于确定的手形图像的形状信息和位置信息。
    • 10. 发明授权
    • Human tracking device, human tracking method and recording medium recording program thereof
    • 人体跟踪装置,人体跟踪方法及其记录介质记录程序
    • US06704433B2
    • 2004-03-09
    • US09741384
    • 2000-12-20
    • Hideaki MatsuoKazuyuki ImagawaYuji Takata
    • Hideaki MatsuoKazuyuki ImagawaYuji Takata
    • G06K900
    • G06K9/00369G01S3/7865G06T7/20
    • A human tracking device according to the present invention stably tracks a human with good perception of the distance to a human with high resistance against disturbance. A camera image is divided into a human region and a background region. Then, each area of the image is judged whether or not the human region can be divided into a plurality of blob models corresponding to parts of a human. The parts of a human are preferably the head, trunk and legs. When the result of the judgment is “YES”, a plurality of human blob models are produced based on the human region. When the result of the judgment is “NO”, a single human blob model is produced based on the human region. The human is then tracked based on these human blob models. In this way, the human can be stably tracked with good perception of the distance to the human and with high resistance against disturbance.
    • 根据本发明的人体跟踪装置稳定地跟踪具有高抗干扰能力的对人的距离的良好感知的人。 相机图像被分为人类区域和背景区域。 然后,判断图像的每个区域是否可以将人类区域划分为与人的部分对应的多个斑点模型。 人的部分最好是头,躯干和腿。 当判断结果为“是”时,基于人类区域产生多个人体斑块模型。 当判断结果为“否”时,基于人类区域产生单个人体斑块模型。 然后基于这些人类斑块模型跟踪人类。 通过这种方式,可以很好地跟踪对人的距离和高抗干扰能力的人的追踪。