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    • 1. 发明申请
    • METHOD AND DEVICE FOR DETERMINING A SHAPE MATCH IN THREE DIMENSIONS
    • 用于确定三维尺寸形状匹配的方法和装置
    • US20120033873A1
    • 2012-02-09
    • US13264803
    • 2010-06-04
    • Ryosuke OzekiHironobu Fujiyoshi
    • Ryosuke OzekiHironobu Fujiyoshi
    • G06K9/00
    • G06K9/00214
    • Provided are a method and a device for determining a shape match in three dimensions, which can utilize information relating to three-dimensional shapes effectively. Camera control means (33) of a determination device (10) captures a range image of an object as a determination target by using a range imaging camera (20). Feature point extraction means (34) extracts feature points based on the range image. Feature amount determination means (35) calculates a three-dimensional shape around the feature point as depths of surface points and determines a feature amount of the feature point based on the depths of the surface points. Match determination means (36) determines the match therebetween based on the feature amounts of the two shapes.
    • 提供了一种用于确定三维形状匹配的方法和装置,其可以有效地利用与三维形状有关的信息。 确定装置(10)的相机控制装置(33)通过使用范围成像照相机(20)捕获作为确定目标的对象的范围图像。 特征点提取装置(34)基于范围图像提取特征点。 特征量确定装置(35)计算特征点周围的三维形状作为表面点的深度,并且基于表面点的深度确定特征点的特征量。 匹配确定装置(36)基于两个形状的特征量确定它们之间的匹配。
    • 2. 发明授权
    • Apparatus for recognizing object in image
    • 用于识别图像中的物体的装置
    • US08027514B2
    • 2011-09-27
    • US12080936
    • 2008-04-07
    • Masanari TakakiHironobu Fujiyoshi
    • Masanari TakakiHironobu Fujiyoshi
    • G06K9/00G06K9/68
    • G06K9/00818G06K9/4671
    • An object recognition apparatus sets each of keypoints extracted from a typical image and one of keypoints extracted from an input image, having scale invariant features similar to each other, as a typical corresponding point and an object corresponding point matching with each other, and produces a position vector directed from a typical reference point of the typical image to each typical keypoint. The apparatus determines a position of an object reference point in the input image from a position of each object corresponding point and the vector of the typical corresponding point matching with the object corresponding point. When the positions of the object reference point are concentrated, the apparatus judges that an object picture having the object corresponding points in the input image matches with the typical image, and the apparatus recognizes the picture as an object indicated by the typical image.
    • 对象识别装置将从典型图像提取的关键点和从具有彼此类似的尺度不变特征的输入图像提取的关键点中的每一个作为典型对应点和对象对应点彼此匹配, 从典型图像的典型参考点引导到每个典型关键点的位置矢量。 该装置从每个对象对应点的位置和与对象对应点匹配的典型对应点的向量确定输入图像中的对象参考点的位置。 当对象参考点的位置集中时,设备判断出具有与输入图像中的对应点相对应的对象图像与典型图像匹配,并且该装置将该图像识别为典型图像所指示的对象。
    • 4. 发明授权
    • Object detection device
    • 物体检测装置
    • US08611604B2
    • 2013-12-17
    • US13375391
    • 2010-06-02
    • Hironobu Fujiyoshi
    • Hironobu Fujiyoshi
    • G06K9/00
    • G06K9/4642G01S7/4802G01S17/89G06K9/00201G06K9/00369G06T7/70G06T2207/10028G06T2207/20021
    • A depth histogram is created for each of a plurality of local regions of the depth image by grouping, according to specified depths, the depth information for the individual pixels that are contained in the local regions. A degree of similarity between two of the depth histograms for two of the local regions at different positions in the depth image is calculated as a feature. A depth image for training that has a high degree of certainty is defined as a positive example, a depth image for training that has a low degree of certainty is defined as a negative example, a classifier that is suitable for classifying the positive example and the negative example is constructed, and an object that is a target of detection is detected in the depth image, using the classifier and based on the feature.
    • 根据指定的深度,分组包含在局部区域中的各个像素的深度信息,为深度图像的多个局部区域中的每一个创建深度直方图。 计算深度图像中不同位置处的两个局部区域的两个深度直方图之间的相似程度作为特征。 将具有高度确定性的训练的深度图像定义为积极的例子,将具有低确定性的训练的深度图像定义为否定示例,适合于对正例进行分类的分类器 构建负的例子,并且使用分类器并且基于特征在深度图像中检测作为检测对象的对象。
    • 5. 发明申请
    • OBJECT DETECTION DEVICE
    • 对象检测装置
    • US20120076361A1
    • 2012-03-29
    • US13375391
    • 2010-06-02
    • Hironobu Fujiyoshi
    • Hironobu Fujiyoshi
    • G06K9/00
    • G06K9/4642G01S7/4802G01S17/89G06K9/00201G06K9/00369G06T7/70G06T2207/10028G06T2207/20021
    • A depth histogram is created for each of a plurality of local regions of the depth image by grouping, according to specified depths, the depth information for the individual pixels that are contained in the local regions. A degree of similarity between two of the depth histograms for two of the local regions at different positions in the depth image is calculated as a feature. A depth image for training that has a high degree of certainty is defined as a positive example, a depth image for training that has a low degree of certainty is defined as a negative example, a classifier that is suitable for classifying the positive example and the negative example is constructed, and an object that is a target of detection is detected in the depth image, using the classifier and based on the feature.
    • 根据指定的深度,分组包含在局部区域中的各个像素的深度信息,为深度图像的多个局部区域中的每一个创建深度直方图。 计算深度图像中不同位置处的两个局部区域的两个深度直方图之间的相似程度作为特征。 将具有高度确定性的训练的深度图像定义为积极的例子,将具有低确定性的训练的深度图像定义为否定示例,适合于对正例进行分类的分类器 构建负的例子,并且使用分类器并且基于特征在深度图像中检测作为检测对象的对象。
    • 6. 发明授权
    • Ellipsoid detecting method, figure center detecting method, image recognizing device, and controller based on image
    • 椭圆体检测方法,图形中心检测方法,图像识别装置和基于图像的控制器
    • US07668337B2
    • 2010-02-23
    • US11512482
    • 2006-08-30
    • Naoki FukayaHironobu FujiyoshiYuusuke SakashitaHisanori Takamaru
    • Naoki FukayaHironobu FujiyoshiYuusuke SakashitaHisanori Takamaru
    • G06K9/00G09B23/02
    • G06K9/00604G06K9/6205
    • A method for detecting an ellipsoid includes: extracting an ellipsoid candidate; extracting an ellipsoid contour; calculating an ellipsoid parameter; calculating an adaptability ratio; and eliminating the ellipsoid candidate. Extracting the ellipsoid candidate includes: inputting an image with figures; selecting the ellipsoid candidate from the figures; and extracting a contour candidate point and a center point. Extracting the ellipsoid contour includes: drawing straight lines; determining contour candidate points; calculating first and second distances; and defining ellipsoid contour points. Calculating the ellipsoid parameter is based on the ellipsoid contour points and the center point. Calculating the adaptability ratio includes: drawing a complete ellipsoid; and calculating the adaptability ratio between the complete ellipsoid and the ellipsoid candidate. Eliminating the ellipsoid candidate is performed when the adaptability ratio is equal to or smaller than a threshold.
    • 一种用于检测椭球的方法包括:提取椭球候选; 提取椭球轮廓; 计算椭球参数; 计算适应性比率; 并消除椭球候选。 提取椭球候选者包括:用图形输入图像; 从图中选择椭球候选者; 并提取轮廓候选点和中心点。 提取椭球轮廓包括:绘制直线; 确定轮廓候选点; 计算第一和第二距离; 并定义椭圆轮廓点。 计算椭球参数是基于椭球轮廓点和中心点。 计算适应性比例包括:绘制完整的椭圆体; 并计算完整椭球和椭球候选的适应度比。 当适应性比例等于或小于阈值时,执行消除椭球候选。
    • 10. 发明申请
    • Apparatus for recognizing object in image
    • 用于识别图像中的物体的装置
    • US20080247651A1
    • 2008-10-09
    • US12080936
    • 2008-04-07
    • Masanari TakakiHironobu Fujiyoshi
    • Masanari TakakiHironobu Fujiyoshi
    • G06K9/68
    • G06K9/00818G06K9/4671
    • An object recognition apparatus sets each of keypoints extracted from a typical image and one of keypoints extracted from an input image, having scale invariant features similar to each other, as a typical corresponding point and an object corresponding point matching with each other, and produces a position vector directed from a typical reference point of the typical image to each typical keypoint. The apparatus determines a position of an object reference point in the input image from a position of each object corresponding point and the vector of the typical corresponding point matching with the object corresponding point. When the positions of the object reference point are concentrated, the apparatus judges that an object picture having the object corresponding points in the input image matches with the typical image, and the apparatus recognizes the picture as an object indicated by the typical image.
    • 对象识别装置将从典型图像提取的关键点和从具有彼此类似的尺度不变特征的输入图像提取的关键点中的每一个作为典型对应点和对象对应点彼此匹配, 从典型图像的典型参考点引导到每个典型关键点的位置矢量。 该装置从每个对象对应点的位置和与对象对应点匹配的典型对应点的向量确定输入图像中的对象参考点的位置。 当对象参考点的位置集中时,设备判断出具有与输入图像中的对应点相对应的对象图像与典型图像匹配,并且该装置将该图像识别为典型图像所指示的对象。