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    • 3. 发明申请
    • IMAGE PROCESSING SYSTEM AND METHOD
    • 图像处理系统和方法
    • US20120251003A1
    • 2012-10-04
    • US13408541
    • 2012-02-29
    • Frank PerbetAtsuto MakiMinh-Tri PhamBjorn StengerOliver Woodford
    • Frank PerbetAtsuto MakiMinh-Tri PhamBjorn StengerOliver Woodford
    • G06K9/34
    • G06K9/6224G06T7/11G06T7/162G06T7/187
    • A method dividing an image into plural superpixels of plural pixels of the image. The method calculates an initial set of weights from a measure of similarity between pairs of pixels, from which a resultant set of weights is calculated for pairs of pixels that are less that a threshold distance apart on the image. The calculation calculates a weight for a pair of pixels as the sum over a set of third pixels of the product of initial weight of the first pixel of the pair of pixel with the third pixel and the weight of the third pixel with the second pixel. Each weight is then subjected to a power coefficient operation. The resultant set of weights and the initial set of weights are then compared to check for convergence. If the weights converge, the converged set of weights is used to divide the image into superpixels.
    • 将图像分割成图像的多个像素的多个超像素的方法。 该方法根据像素对之间的相似性的度量来计算初始权重集合,对于图像上的阈值距离小的像素对,计算出所得到的权重集合。 该计算计算一对像素的权重,作为该对像素与第三像素的第一像素的初始权重乘积与第三像素与第二像素的权重的乘积的一组第三像素之和。 然后对每个重量进行功率系数运算。 然后将所得到的权重集和初始权重集合进行比较以检查收敛。 如果权重收敛,则使用收敛的权重集合将图像分割成超像素。
    • 4. 发明申请
    • IMAGE PROCESSING METHOD AND SYSTEM
    • 图像处理方法和系统
    • US20130016913A1
    • 2013-01-17
    • US13407357
    • 2012-02-28
    • Minh-Tri PhamOliver WoodfordFrank PerbetAtsuto MakiBjorn StengerRoberto Cipolla
    • Minh-Tri PhamOliver WoodfordFrank PerbetAtsuto MakiBjorn StengerRoberto Cipolla
    • G06K9/68
    • G06T7/0042G06F17/30259G06K9/00214G06K9/2036G06K9/6202G06T3/20G06T3/60G06T7/586G06T7/73G06T2207/10024G06T2207/30208G06T2207/30244
    • A method of comparing two object poses, wherein each object pose is expressed in terms of position, orientation and scale with respect to a common coordinate system, the method comprising:calculating a distance between the two object poses, the distance being calculated using the distance function: d sRt  ( X , Y ) = d s 2  ( X , Y ) σ s 2 + d r 2  ( X , Y ) σ r 2 + d t 2  ( X , Y ) σ t 2 . where X is the object pose of one object and Y is the object pose of the other object, d s  ( X , Y ) =  log  ( s  ( X ) s  ( Y ) )  ,  d r  ( X , Y ) =  R  ( X ) - R  ( Y )  F ,  d t  ( X , Y ) =  t  ( X ) - t  ( Y )  s  ( Y ) , s(X) and s(Y) are scalar functions representing the scale of the object poses X and Y respectively, R(X) and R(Y) are matrices expressing the rotation of object poses X and Y respectively, t(X) and t(Y) are vectors expressing the translation of object poses X and Y respectively, and σs, or and σt are weighting factors for ds, dr and dt respectively.
    • 一种比较两个物体姿态的方法,其中每个物体姿态相对于公共坐标系以位置,方向和比例表示,所述方法包括:计算两个物体姿势之间的距离,使用距离计算距离 函数:d sRt(X,Y)= ds 2(X,Y)&sgr; s 2 + d r 2(X,Y)&sgr; r 2 + d t 2(X,Y)&sgr; t 2。 其中X是一个对象的对象姿态,Y是另一个对象的对象姿态,其中X(X,Y)=(log)(s(X)s(Y)),dr (Y)(X) - R(Y)F,dt(X,Y)=t(X) - t(Y) )和s(Y)分别表示对象姿态X和Y的尺度的标量函数,R(X)和R(Y)分别表示对象姿势X和Y的旋转矩阵,t(X)和t( Y)是分别表示对象姿势X和Y的平移的矢量,&sgr,s,和&sgr; t分别是ds,dr和dt的加权因子。
    • 5. 发明申请
    • IMAGE ANALYSIS METHOD
    • 图像分析方法
    • US20120224744A1
    • 2012-09-06
    • US13389018
    • 2009-08-06
    • Frank PerbetAtsuto MakiBjorn Stenger
    • Frank PerbetAtsuto MakiBjorn Stenger
    • G06K9/62
    • G06T7/2033G06T7/246G06T7/277
    • A moving feature is recognized in a video sequence by comparing its movement with a characteristic pattern. Possible trajectories through the video sequence are generated for an object by identifying potential matches of points in pairs of frames of the video sequence. When looking for the characteristic pattern, a number of possible trajectories are analyzed. The possible trajectories may be selected so that they are suitable for analysis. This may include selecting longer trajectories that can be easier to analyze. Thereby where the object being tracked is momentarily behind another object a continuous trajectory is generated.
    • 通过将其移动与特征图案进行比较,在视频序列中识别移动特征。 通过识别视频序列的帧对中的点的潜在匹配,通过视频序列生成对于对象的可能的轨迹。 在寻找特征模式时,分析了一些可能的轨迹。 可以选择可能的轨迹,使得它们适合于分析。 这可能包括选择更容易分析的更长的轨迹。 因此,被跟踪物体暂时在另一物体后方产生连续的轨迹。
    • 7. 发明授权
    • Image processing system and method
    • 图像处理系统和方法
    • US08712154B2
    • 2014-04-29
    • US13408541
    • 2012-02-29
    • Frank PerbetAtsuto MakiMinh-Tri PhamBjorn StengerOliver Woodford
    • Frank PerbetAtsuto MakiMinh-Tri PhamBjorn StengerOliver Woodford
    • G06K9/34
    • G06K9/6224G06T7/11G06T7/162G06T7/187
    • A method dividing an image into plural superpixels of plural pixels of the image. The method calculates an initial set of weights from a measure of similarity between pairs of pixels, from which a resultant set of weights is calculated for pairs of pixels that are less that a threshold distance apart on the image. The calculation calculates a weight for a pair of pixels as the sum over a set of third pixels of the product of initial weight of the first pixel of the pair of pixel with the third pixel and the weight of the third pixel with the second pixel. Each weight is then subjected to a power coefficient operation. The resultant set of weights and the initial set of weights are then compared to check for convergence. If the weights converge, the converged set of weights is used to divide the image into superpixels.
    • 将图像分割成图像的多个像素的多个超像素的方法。 该方法根据像素对之间的相似性的度量来计算初始权重集合,对于图像上的阈值距离小的像素对,计算出所得到的权重集合。 该计算计算一对像素的权重,作为该对像素与第三像素的第一像素的初始权重乘积与第三像素与第二像素的权重的乘积的一组第三像素之和。 然后对每个重量进行功率系数运算。 然后将所得到的权重集和初始权重集合进行比较以检查收敛。 如果权重收敛,则使用收敛的权重集合将图像分割成超像素。
    • 8. 发明申请
    • OBJECT LOCATION METHOD AND SYSTEM
    • 对象位置方法和系统
    • US20130051639A1
    • 2013-02-28
    • US13408479
    • 2012-02-29
    • Oliver WoodfordMinh-Tri PhamAtsuto MakiFrank PerbetBjorn Stenger
    • Oliver WoodfordMinh-Tri PhamAtsuto MakiFrank PerbetBjorn Stenger
    • G06K9/68G06K9/46
    • G06K9/6277G06K9/4633G06K9/6244
    • An object location method includes: analysing data including plural objects each including plural features, and extracting the features from the data; matching features stored in a database with those extracted from the data, and deriving a prediction of the object, each feature extracted from the data providing a vote for at least one prediction; expressing the prediction to be analysed in a Hough space, the objects to be analysed being described by n parameters and each parameter defining a dimension of the Hough space, n is an integer of at least one; providing a constraint by applying a higher weighting to votes which agree with votes from other features than those votes which do not agree with votes from other features; finding local maxima in the Hough space using the weighted votes; and identifying the predictions associated with the local maxima to locate the objects provided in the data.
    • 对象定位方法包括:分析包括多个对象的数据,每个对象包括多个特征,并从数据中提取特征; 存储在数据库中的匹配特征与从数据中提取的匹配特征,以及导出对象的预测,从提供至少一个预测的投票的数据中提取的每个特征; 表示要在霍夫空间中分析的预测,由n个参数描述待分析对象,并且每个参数定义霍夫空间的维度,n是至少一个的整数; 通过对与其他功能的票数一致的票数比不符合其他特征票的票数更高的权重给予约束; 使用加权票在霍夫空间找到本地最大值; 并且识别与局部最大值相关联的预测以定位数据中提供的对象。