Light transport reconstruction from sparsely captured images
    52.
    发明授权
    Light transport reconstruction from sparsely captured images 有权
    从稀疏捕获的图像的光传输重建

    公开(公告)号:US08406556B2

    公开(公告)日:2013-03-26

    申请号:US12797859

    申请日:2010-06-10

    IPC分类号: G06K9/40

    CPC分类号: G06T15/50

    摘要: A “Scene Re-Lighter” provides various techniques for using an automatically reconstructed light transport matrix derived from a sparse sampling of images to provide various combinations of complex light transport effects in images, including caustics, complex occlusions, inter-reflections, subsurface scattering, etc. More specifically, the Scene Re-Lighter reconstructs the light transport matrix from a relatively small number of acquired images using a “Kernel Nyström” based technique adapted for low rank matrices constructed from sparsely sampled images. A “light transport kernel” is incorporated into the Nyström method to exploit nonlinear coherence in the light transport matrix. Further, an adaptive process is used to efficiently capture the sparsely sampled images from a scene. The Scene Re-Lighter is capable of achieving good reconstruction of the light transport matrix with only few hundred images to produce high quality relighting results. Further, the Scene Re-Lighter is also effective for modeling scenes with complex lighting effects and occlusions.

    摘要翻译: 场景再打火机提供了使用从图像稀疏采样得到的自动重建光传输矩阵的各种技术,以提供图像中复杂光传输效应的各种组合,包括焦散,复杂遮挡,相互反射,地下散射等。 更具体地说,场景重新点亮器使用适用于由稀疏采样图像构成的低秩矩阵的基于内核Nyström的技术,从相对较少数量的获取图像重构光传输矩阵。 光传输核被并入Nyström方法,以利用光传输矩阵中的非线性相干性。 此外,使用自适应处理来有效地从场景捕获稀疏采样的图像。 场景重新打火机能够通过仅仅几百张图像实现光传输矩阵的良好重建,从而产生高品质的重视效果。 此外,场景重新打火机对于对具有复杂的照明效果和遮挡的场景进行建模也是有效的。

    Annotation Detection and Anchoring on Ink Notes
    53.
    发明申请
    Annotation Detection and Anchoring on Ink Notes 有权
    墨迹注解检测和锚定

    公开(公告)号:US20120201459A1

    公开(公告)日:2012-08-09

    申请号:US13447968

    申请日:2012-04-16

    IPC分类号: G06K9/34

    CPC分类号: G06F17/242

    摘要: Systems and methods for detecting annotation digital ink strokes and further associating annotation digital ink strokes with word digital ink strokes are presented. Ink strokes are captured on a writing surface and then classified as words or annotations. Annotations are then anchored to corresponding words. When words are relocated or edited on the writing surface, the anchored annotations are also relocated and may even be reshaped according to the changes in the anchored words.

    摘要翻译: 提出了用于检测注释数字墨水笔画并进一步将注释数字墨迹与字数字笔墨相关联的系统和方法。 墨水笔画被捕获在书写表面上,然后分类为单词或注释。 然后将注释锚定到相应的词。 当在书写表面上重新定位或编辑单词时,锚定的注释也被重定位,甚至可以根据锚定单词的变化进行重新整形。

    Global metadata embedding and decoding
    54.
    发明授权
    Global metadata embedding and decoding 有权
    全球元数据嵌入和解码

    公开(公告)号:US08156153B2

    公开(公告)日:2012-04-10

    申请号:US12180484

    申请日:2008-07-25

    IPC分类号: G06F7/00 G06F17/00 G06K9/00

    摘要: Global metadata, such as a document identifier, which may be a globally unique identifier, is embedded into an embedded interactive code document by combining a first m-array and a plurality of copies of the first m-array to generate a combined m-array with encoded global metadata such that respective start positions (xd, yd)i of the plurality of copies of the first m-array in the combined m-array are each shifted, by respective amounts that are based on respective portions of the global metadata, relative to a start position of the first m-array in the combined m-array. Global metadata may be decoded from the combined m-array by determining the respective amounts by which the plurality of copies of the first m-array are shifted, relative to the first m-array, in the combined m-array and by combining the respective amounts to produce a decoded value of the global metadata.

    摘要翻译: 通过组合第一m阵列和第一m阵列的多个副本来将全局元数据(诸如可以是全球唯一标识符的文档标识符)嵌入到嵌入式交互式代码文档中以生成组合的m阵列 具有编码的全局元数据,使得组合的m阵列中的第一m阵列的多个副本中的各个开始位置(xd,yd)i分别被移动,基于全局元数据的相应部分的相应量, 相对于组合的m阵列中的第一m阵列的开始位置。 可以通过确定在组合的m阵列中第一m阵列的多个副本相对于第一m阵列移位的相应量,并通过组合相应的数组来组合全局元数据 相当于产生全局元数据的解码值。

    Laplacian principal components analysis (LPCA)
    55.
    发明授权
    Laplacian principal components analysis (LPCA) 有权
    拉普拉斯主成分分析(LPCA)

    公开(公告)号:US08064697B2

    公开(公告)日:2011-11-22

    申请号:US11871764

    申请日:2007-10-12

    IPC分类号: G06K9/00 G06T7/00

    CPC分类号: G06K9/6248

    摘要: Systems and methods perform Laplacian Principal Components Analysis (LPCA). In one implementation, an exemplary system receives multidimensional data and reduces dimensionality of the data by locally optimizing a scatter of each local sample of the data. The optimization includes summing weighted distances between low dimensional representations of the data and a mean. The weights of the distances can be determined by a coding length of each local data sample. The system can globally align the locally optimized weighted scatters of the local samples and provide a global projection matrix. The LPCA improves performance of such applications as face recognition and manifold learning.

    摘要翻译: 系统和方法执行拉普拉斯主成分分析(LPCA)。 在一个实现中,示例性系统通过局部优化数据的每个局部采样的散射来接收多维数据并且降低数据的维度。 优化包括对数据的低维表示和平均值之间的加权距离求和。 距离的权重可以通过每个本地数据样本的编码长度来确定。 该系统可以对局部采样的局部优化加权散射进行全局对齐,并提供全局投影矩阵。 LPCA可以改善诸如面部识别和歧管学习等应用的性能。

    Script recognition for ink notes
    56.
    发明授权
    Script recognition for ink notes 有权
    油墨笔记的脚本识别

    公开(公告)号:US07929769B2

    公开(公告)日:2011-04-19

    申请号:US11301761

    申请日:2005-12-13

    IPC分类号: G06K9/00 G06K9/48 G06K9/62

    摘要: Computer-readable media having computer-executable instructions distinguish the script type of at least one portion of a writing input. At least one sub-word of a writing line of a handwritten document is identified and is processed to determine the associated writing style that includes a cursive writing style and a hand-printed writing style. The writing line is consequently associated with a script type. The script type of a writing line is determined from the script types of the sub-words in the writing line. When the number of sub-words having a first script type is greater than the number of sub-words having a second script type, the script type of the writing line is categorized as the first script type. In addition, a script analyzer determines a writing style of at least one sub-word and selects one of a plurality of neural networks to categorize the script type of a writing line.

    摘要翻译: 具有计算机可执行指令的计算机可读介质区分写入输入的至少一部分的脚本类型。 识别手写文件的写作线的至少一个子词,并被处理以确定包括草书写作风格和手写书写风格的相关联的书写风格。 因此,写作行与脚本类型相关联。 写作行的脚本类型由写入行中的子字的脚本类型确定。 当具有第一脚本类型的子字的数量大于具有第二脚本类型的子字的数量时,写入行的脚本类型被分类为第一脚本类型。 此外,脚本分析器确定至少一个子字的写入风格,并且选择多个神经网络中的一个以对写入线的脚本类型进行分类。

    COMPUTING MINIMAL POLYNOMIALS OF RADICAL EXPRESSIONS
    57.
    发明申请
    COMPUTING MINIMAL POLYNOMIALS OF RADICAL EXPRESSIONS 审中-公开
    计算放射性表达的最小多边形

    公开(公告)号:US20100198902A1

    公开(公告)日:2010-08-05

    申请号:US12364533

    申请日:2009-02-03

    IPC分类号: G06F7/552

    CPC分类号: G06F17/10

    摘要: Described is a technology, such as implemented in a computational software program, by which a minimal polynomial is efficiently determined for a radical expression based upon its structure of the radical expression. An annihilation polynomial is found based upon levels of the radical to obtain roots of the radical. A numerical method performs a zero test or multiple zero tests to find the minimal polynomial. In one implementation, the set of roots corresponding to a radical expression is found. The annihilation polynomial is computed by grouping roots of the set according to their conjugation relationship and multiplying factor polynomials level by level. A selection mechanism selects the minimal polynomial based upon the annihilation polynomial's factors.

    摘要翻译: 描述了一种技术,例如在计算软件程序中实现的技术,通过该技术,基于其基本表达式的结构,有效地确定基本表达式的最小多项式。 基于获得根的根的自由基的水平找到湮灭多项式。 数值方法执行零测试或多零测试以找到最小多项式。 在一个实现中,找到与激进表达相对应的一组根。 湮灭多项式通过根据它们的共轭关系和乘法因子多项式级别逐级分组的根来计算。 选择机制根据湮灭多项式的因素选择最小多项式。

    TENSOR LINEAR LAPLACIAN DISCRIMINATION FOR FEATURE EXTRACTION
    60.
    发明申请
    TENSOR LINEAR LAPLACIAN DISCRIMINATION FOR FEATURE EXTRACTION 有权
    用于特征提取的传感器线性拉普拉斯分析

    公开(公告)号:US20100076723A1

    公开(公告)日:2010-03-25

    申请号:US12235927

    申请日:2008-09-23

    CPC分类号: G06F17/30598 G06K9/6234

    摘要: Tensor linear Laplacian discrimination for feature extraction is disclosed. One embodiment comprises generating a contextual distance based sample weight and class weight, calculating a within-class scatter using the at least one sample weight and a between-class scatter for multiple classes of data samples in a sample set using the class weight, performing a mode-k matrix unfolding on scatters and generating at least one orthogonal projection matrix.

    摘要翻译: 公开了用于特征提取的张量线性拉普拉斯判别。 一个实施例包括生成基于上下文距离的样本权重和类权重,使用所述至少一个样本权重来计算类内散度,以及使用类权重在样本集合中的多类数据样本之间进行类间散射,执行 mode-k矩阵在散射上展开并生成至少一个正交投影矩阵。