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    Method and system for filtering, registering, and matching 2.5D normal maps
    1.
    发明授权
    Method and system for filtering, registering, and matching 2.5D normal maps 有权
    用于过滤，注册和匹配2.5D法线贴图的方法和系统

    公开(公告)号：US07844133B2

    公开(公告)日：2010-11-30

    申请号：US12604876

    申请日：2009-10-23

    申请人： Clay Douglas Spence ,  Craig Langdale Fancourt

    发明人： Clay Douglas Spence ,  Craig Langdale Fancourt

    IPC分类号： G06K9/32

    CPC分类号： G06K9/00214 ,  G06T7/33 ,  G06T2200/04

    摘要： An iterative approach to vector median filtering wherein the resulting median vector need not be a member of the original data set. The iterative vector median filtering allows for fast convergence for complex computations and an output which is approximate to the mean, particularly for small data sets.In addition, a method and system for registering and matching 2.5 normal maps is provided. Registration of two maps is performed by optimally aligning their normals through 2-D warping in the image plane in conjunction with a 3-D rotation of the normals. Once aligned, the average dot-product serves as a matching metric for automatic target recognition (ATR).

    摘要翻译： 矢量中值滤波的迭代方法，其中所得到的中值向量不需要是原始数据集的成员。 迭代向量中值滤波允许复杂计算的快速收敛和近似于平均值的输出，特别是对于小数据集。 另外，提供了一种用于注册和匹配2.5法线贴图的方法和系统。 通过将图像平面中的二维翘曲与法线的3-D旋转结合来最佳地对准其法线来执行两个地图的注册。 一旦对齐，平均点积用作自动目标识别（ATR）的匹配度量。

    Method and system for filtering, registering, and matching 2.5D normal maps
    2.
    发明授权
    Method and system for filtering, registering, and matching 2.5D normal maps 失效

    公开(公告)号：US07747106B2

    公开(公告)日：2010-06-29

    申请号：US11451671

    申请日：2006-06-13

    申请人： Clay Douglas Spence ,  Craig Langdale Fancourt

    发明人： Clay Douglas Spence ,  Craig Langdale Fancourt

    IPC分类号： G06K9/32

    CPC分类号： G06K9/00214 ,  G06T7/33 ,  G06T2200/04

    摘要： An iterative approach to vector median filtering wherein the resulting median vector need not be a member of the original data set. The iterative vector median filtering allows for fast convergence for complex computations and an output which is approximate to the mean, particularly for small data sets.In addition, a method and system for registering and matching 2.5 normal maps is provided. Registration of two maps is performed by optimally aligning their normals through 2-D warping in the image plane in conjunction with a 3-D rotation of the normals. Once aligned, the average dot-product serves as a matching metric for automatic target recognition (ATR).

    Method and system for on-line blind source separation
    3.
    发明授权
    Method and system for on-line blind source separation 有权
    在线盲源分离方法与系统

    公开(公告)号：US07603401B2

    公开(公告)日：2009-10-13

    申请号：US11095346

    申请日：2005-03-31

    申请人： Lucas Cristobal Parra ,  Clay Douglas Spence

    发明人： Lucas Cristobal Parra ,  Clay Douglas Spence

    IPC分类号： G06F15/10 ,  G06F17/10

    CPC分类号： G06K9/6243 ,  G10L21/0272 ,  H03H21/0012 ,  H03H21/0029 ,  H03H2021/0034

    摘要： A method and apparatus is disclosed for performing blind source separation using convolutive signal decorrelation. For a first embodiment, the method accumulates a length of input signal (mixed signal) that comprises a plurality of independent signals from independent signal sources. The invention then divides the length of input signal into a plurality of T-length periods (windows) and performs a discrete Fourier transform (DFT) on the signal within each T-length period. Thereafter, estimated cross-correlation values are computed using a plurality of the averaged DFT values. A total number of K cross-correlation values are computed, where each of the K values is averaged over N of the T-length periods. Using the cross-correlation values, a gradient descent process computes the coefficients of a FIR filter that will effectively separate the source signals within the input signal. A second embodiment of the invention is directed to on-line processing of the input signal—i.e., processing the signal as soon as it arrives with no storage of the signal data. In particular, an on-line gradient algorithm is provided for application to non-stationary signals and having an adaptive step size in the frequency domain based on second derivatives of the cost function. The on-line separation methodology of this embodiment is characterized as multiple adaptive decorrelation.

    摘要翻译： 公开了一种使用卷积信号去相关进行盲源分离的方法和装置。 对于第一实施例，该方法累积包括来自独立信号源的多个独立信号的输入信号（混合信号）的长度。 然后，本发明将输入信号的长度划分成多个T长度周期（窗口），并对每个T长度周期内的信号执行离散付里叶变换（DFT）。 此后，使用多个平均DFT值来计算估计的互相关值。 计算总共K个互相关值，其中K个值中的每一个在T个长度周期的N个上被平均。 使用互相关值，梯度下降处理计算将有效地分离输入信号内的源信号的FIR滤波器的系数。 本发明的第二个实施例涉及输入信号的在线处理，即，一旦信号到达就处理该信号而没有信号数据的存储。 特别地，提供在线梯度算法用于非平稳信号的应用，并且基于成本函数的二阶导数在频域中具有自适应步长。 本实施例的在线分离方法被表征为多自适应去相关。

    Method and system for on-line blind source separation
    5.
    发明授权
    Method and system for on-line blind source separation 有权
    在线盲源分离方法与系统

    公开(公告)号：US06898612B1

    公开(公告)日：2005-05-24

    申请号：US09597105

    申请日：2000-06-20

    申请人： Lucas Cristobal Parra ,  Clay Douglas Spence

    发明人： Lucas Cristobal Parra ,  Clay Douglas Spence

    IPC分类号： G05B23/02 ,  G06F17/14 ,  G06K9/62 ,  G10L21/02 ,  H03H21/00 ,  G06F15/00 ,  G06F17/10

    CPC分类号： G06K9/6243 ,  G10L21/0272 ,  H03H21/0012 ,  H03H21/0029 ,  H03H2021/0034

    摘要： A method and apparatus is disclosed for performing blind source separation using convolutive signal decorrelation. For a first embodiment, the method accumulates a length of input signal (mixed signal) that includes a plurality of independent signals from independent signal sources. The invention then divides the length of input signal into a plurality of T-length periods (windows) and performs a discrete Fourier transform (DFT) on the, signal within each T-length period. Thereafter, estimated cross-correlation values are computed using a plurality of the averaged DFT values. A total number of K cross-correlation values are computed, where each of the K values is averaged over N of the T-length periods. Using the cross-correlation values, a gradient descent process computes the coefficients of a finite impulse response (FIR) filter that will effectively separate the source signals within the input signal. A second embodiment of the invention is directed to on-line processing of the input signal—i.e., processing the signal as soon as it arrives with no storage of the signal data. In particular, an on-line gradient algorithm is provided for application to non-stationary signals and having an adaptive step size in the frequency domain based on second derivatives of the cost function. The on-line separation methodology of this embodiment is characterized as multiple adaptive decorrelation.

    摘要翻译： 公开了一种使用卷积信号去相关进行盲源分离的方法和装置。 对于第一实施例，该方法累积包括来自独立信号源的多个独立信号的输入信号（混合信号）的长度。 然后，本发明将输入信号的长度划分成多个T长度周期（窗口），并在每个T长度周期内对该信号执行离散付里叶变换（DFT）。 此后，使用多个平均DFT值来计算估计的互相关值。 计算总共K个互相关值，其中K个值中的每一个在T个长度周期的N个上被平均。 使用互相关值，梯度下降处理计算有效脉冲响应（FIR）滤波器的系数，其将有效地分离输入信号内的源信号。 本发明的第二个实施例涉及输入信号的在线处理，即，一旦信号到达就处理该信号而没有信号数据的存储。 特别地，提供在线梯度算法用于非平稳信号的应用，并且基于成本函数的二阶导数在频域中具有自适应步长。 本实施例的在线分离方法被表征为多自适应去相关。

    Method and apparatus for image processing by generating probability distribution of images
    6.
    发明授权
    Method and apparatus for image processing by generating probability distribution of images 失效
    通过产生图像的概率分布的图像处理方法和装置

    公开(公告)号：US06704454B1

    公开(公告)日：2004-03-09

    申请号：US09589715

    申请日：2000-06-08

    申请人： Clay Douglas Spence ,  Lucas Parra

    发明人： Clay Douglas Spence ,  Lucas Parra

    IPC分类号： G06K936

    CPC分类号： G06K9/52 ,  G06K9/6857

    摘要： An apparatus and a concomitant method for modeling local and non-local information in an image to compute an image probability distribution for the image is disclosed. In one embodiment, such an image probability distribution is determined in an object recognition system.

    摘要翻译： 公开了一种用于对图像中的局部和非本地信息进行建模以计算图像的图像概率分布的装置和并发方法。 在一个实施例中，在对象识别系统中确定这样的图像概率分布。

    Convolutive blind source separation using a multiple decorrelation method
    7.
    发明授权
    Convolutive blind source separation using a multiple decorrelation method 有权
    卷积盲源分离使用多重去相关方法

    公开(公告)号：US6167417A

    公开(公告)日：2000-12-26

    申请号：US191217

    申请日：1998-11-12

    申请人： Lucas Parra ,  Clay Douglas Spence

    发明人： Lucas Parra ,  Clay Douglas Spence

    IPC分类号： G10L19/00 ,  G06K9/62 ,  H03H21/00 ,  G06F15/00 ,  G06F17/10

    CPC分类号： H03H21/0029 ,  G06K9/624 ,  H03H21/0012 ,  H03H2021/0034

    摘要： A method and apparatus that performs blind source separation using convolutive signal decorrelation. More specifically, the method accumulates a length of input signal (mixed signal) that includes a plurality of independent signals from independent signal sources. The invention then divides the length of input signal into a plurality of T-length periods (windows) and performs a discrete Fourier transform (DFT) on the signal within each T-length period. Thereafter, estimated cross-correlation values are computed using a plurality of the averaged DFT values. A total number of K cross-correlation values are computed, where each of the K values is averaged over N of the T-length periods. Using the cross-correlation values, a gradient descent process computes the coefficients of a finite impulse response (FIR) filter that will effectively separate the source signals within the input signal. To achieve an accurate solution, the gradient descent process is constrained in that the time-domain values of the filter coefficients can attain only certain values, i.e., the time-domain filter coefficient values W(.tau.) are constrained within each T-length period to be zero for any time t>Q. In this manner, a unique solution for the FIR filter coefficients is computed and a filter produced using these coefficients will effectively separate the source signals.

    摘要翻译： 使用卷积信号去相关来执行盲源分离的方法和装置。 更具体地，该方法累积包括来自独立信号源的多个独立信号的输入信号（混合信号）的长度。 然后，本发明将输入信号的长度划分成多个T长度周期（窗口），并对每个T长度周期内的信号执行离散付里叶变换（DFT）。 此后，使用多个平均DFT值来计算估计的互相关值。 计算总共K个互相关值，其中K个值中的每一个在T个长度周期的N个上被平均。 使用互相关值，梯度下降处理计算有效脉冲响应（FIR）滤波器的系数，其将有效地分离输入信号内的源信号。 为了获得准确的解决方案，梯度下降过程受到限制，因为滤波器系数的时域值只能达到某些值，即时域滤波器系数值W（τ）被限制在每个T长周期内 在任何时间t> Q为零。 以这种方式，计算FIR滤波器系数的唯一解，并且使用这些系数产生的滤波器将有效地分离源信号。

    METHOD AND SYSTEM FOR FILTERING, REGISTERING, AND MATCHING 2.5D NORMAL MAPS
    8.
    发明申请
    METHOD AND SYSTEM FOR FILTERING, REGISTERING, AND MATCHING 2.5D NORMAL MAPS 有权
    用于过滤，注册和匹配2.5D正常MAPS的方法和系统

    公开(公告)号：US20100172597A1

    公开(公告)日：2010-07-08

    申请号：US12604876

    申请日：2009-10-23

    申请人： Clay Douglas Spence ,  Craig Langdale Fancourt

    发明人： Clay Douglas Spence ,  Craig Langdale Fancourt

    IPC分类号： G06K9/64

    CPC分类号： G06K9/00214 ,  G06T7/33 ,  G06T2200/04

    摘要： An iterative approach to vector median filtering wherein the resulting median vector need not be a member of the original data set. The iterative vector median filtering allows for fast convergence for complex computations and an output which is approximate to the mean, particularly for small data sets.In addition, a method and system for registering and matching 2.5 normal maps is provided. Registration of two maps is performed by optimally aligning their normals through 2-D warping in the image plane in conjunction with a 3-D rotation of the normals. Once aligned, the average dot-product serves as a matching metric for automatic target recognition (ATR).

    摘要翻译： 矢量中值滤波的迭代方法，其中所得到的中值向量不需要是原始数据集的成员。 迭代向量中值滤波允许复杂计算的快速收敛和近似于平均值的输出，特别是对于小数据集。 另外，提供了一种用于注册和匹配2.5法线贴图的方法和系统。 通过将图像平面中的二维翘曲与法线的3-D旋转结合来最佳地对准其法线来执行两个地图的注册。 一旦对齐，平均点积用作自动目标识别（ATR）的匹配度量。

    Method and apparatus for training a neural network to detect objects in an image
    10.
    发明授权
    Method and apparatus for training a neural network to detect objects in an image 有权
    用于训练神经网络以检测图像中的物体的方法和装置

    公开(公告)号：US06324532B1

    公开(公告)日：2001-11-27

    申请号：US09464506

    申请日：1999-12-15

    申请人： Clay Douglas Spence ,  Paul Sajda

    发明人： Clay Douglas Spence ,  Paul Sajda

    IPC分类号： G06F1518

    CPC分类号： G06K9/3241 ,  G06K9/6278 ,  G06K9/66 ,  G06N3/0454 ,  G06N3/082

    摘要： A signal processing apparatus and concomitant method for learning and integrating features from multiple resolutions for detecting and/or classifying objects. The signal processing apparatus comprises a hierarchical pyramid of neural networks (HPNN) having a “fine-to-coarse” structure or a combination of the “fine-to-coarse” and the “coarse-to-fine” structures.

    摘要翻译： 一种用于学习和整合用于检测和/或分类对象的多个分辨率的特征的信号处理装置和并发方法。 该信号处理装置包括具有“细至粗”结构的神经网络（HPNN）等级金字塔或“细到粗”和“粗到细”结构的组合。