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    • 24. 发明申请
    • IMAGE CAPTURING APPARATUS AND IMAGE CAPTURING METHOD
    • 图像捕获设备和图像捕获方法
    • US20070025722A1
    • 2007-02-01
    • US11459112
    • 2006-07-21
    • Masakazu MatsuguKatsuhiko MoriYuji KanedaTadashi Hayashi
    • Masakazu MatsuguKatsuhiko MoriYuji KanedaTadashi Hayashi
    • G03B17/00
    • G06K9/00248G03B17/16G06K9/00315G06T7/97H04N5/232H04N5/23219H04N5/23222H04N5/772H04N2101/00
    • In an image capturing apparatus, a video input unit (2) captures the image of an object and sequentially acquires image data associated with the image capturing, a model data memory (6) stores model data associated with the first feature quantity calculated from a feature point of the object in a model image, a principal object detection unit (3) calculates the second feature quantity from a feature point of the object in the acquired image data, a state change estimation unit (4) estimates, on the basis of the second feature quantity and the model data, the timing when the object satisfies a predetermined condition, and an image input processing control unit (7) stores the image data corresponding to the estimated timing in an image recording unit (5). This configuration makes the image capturing apparatus acquire an image in a more proper state without large-capacity memory.
    • 在图像捕获装置中,视频输入单元(2)捕获对象的图像并顺序获取与图像拍摄相关联的图像数据,模型数据存储器(6)存储与从特征计算出的第一特征量相关联的模型数据 主体对象检测单元(3)根据所获取的图像数据中的对象的特征点计算第二特征量,状态变化估计单元(4)基于所获取的图像数据 第二特征量和模型数据,对象满足预定条件的定时,图像输入处理控制单元(7)将与估计的定时对应的图像数据存储在图像记录单元(5)中。 该配置使得图像捕获装置在没有大容量存储器的情况下获得更适当状态的图像。
    • 29. 发明授权
    • Pattern recognition apparatus for detecting predetermined pattern contained in input signal
    • 用于检测包含在输入信号中的预定图案的图案识别装置
    • US07039233B2
    • 2006-05-02
    • US10156118
    • 2002-05-29
    • Katsuhiko MoriMasakazu MatsuguOsamu Nomura
    • Katsuhiko MoriMasakazu MatsuguOsamu Nomura
    • G06K9/00G06K9/54
    • G06K9/4628G06K9/00973
    • A pattern recognition apparatus for detecting a predetermined pattern contained in an input signal is provided with plural detecting processing parts and for detecting respectively different features for a same input, plural integrating processing parts for spatially integrating, for each process results, the features detected by the plural detecting processing parts, plural detecting memories for retaining the process results of the detecting processing parts, plural integrating memories for retaining the process results of the integrating processing parts, a global data line 1030 to which all the predetermined detecting processing parts and all the predetermined integrating memories are connected at a certain timing, and plural local data lines each of which is connected to a predetermined set of the detecting processing parts, the integrating processing parts and the detecting memory.
    • 用于检测包含在输入信号中的预定图案的模式识别装置设置有多个检测处理部分,并且用于分别检测相同输入的不同特征,用于对于每个处理结果来对每个处理结果进行空间积分的多个积分处理部分, 多个检测处理部分,用于保持检测处理部分的处理结果的多个检测存储器,用于保持积分处理部分的处理结果的多个积分存储器,全部数据线1030,所有预定检测处理部分和全部预定检测处理部分 积分存储器在一定时间连接,多个本地数据线连接到预定的检测处理部分组,积分处理部分和检测存储器。
    • 30. 发明申请
    • Learning method and device for pattern recognition
    • 用于模式识别的学习方法和设备
    • US20050185835A1
    • 2005-08-25
    • US11044188
    • 2005-01-28
    • Masakazu MatsuguPierre Cardon
    • Masakazu MatsuguPierre Cardon
    • G06T1/00G06K9/46G06K9/62G06N3/00G06T1/40G06T7/00
    • G06K9/4619
    • In learning for pattern recognition, an aggregation of different types of object image data is inputted, and local features having given geometric structures are detected from each object image data inputted. The detected local features are put through clustering, plural representative local features are selected based on results of the clustering, and a learning data set containing the selected representative local features as supervisor data is used to recognize or detect an object that corresponds to the object image data. The learning thus makes it possible to appropriately extract, from an aggregation of images, local features useful for detection and recognition of subjects of different categories.
    • 在学习图形识别时,输入不同类型的对象图像数据的聚合,并且从输入的每个对象图像数据检测具有给定几何结构的局部特征。 检测到的本地特征通过聚类进行,基于聚类的结果选择多个代表性的局部特征,并且使用包含所选择的代表性局部特征作为监督数据的学习数据集来识别或检测与对象图像相对应的对象 数据。 因此,该学习使得可以从图像的聚集中适当地提取对于不同类别的对象的检测和识别有用的局部特征。