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    • 2. 发明授权
    • Spatial recognition and grouping of text and graphics
    • 文本和图形的空间识别和分组
    • US07729538B2
    • 2010-06-01
    • US10927452
    • 2004-08-26
    • Michael ShilmanPaul A. ViolaKumar H. Chellapilla
    • Michael ShilmanPaul A. ViolaKumar H. Chellapilla
    • G06K9/00
    • G06K9/726G06K9/00402G06K9/344G06K9/4614G06K2209/01
    • The present invention leverages spatial relationships to provide a systematic means to recognize text and/or graphics. This allows augmentation of a sketched shape with its symbolic meaning, enabling numerous features including smart editing, beautification, and interactive simulation of visual languages. The spatial recognition method obtains a search-based optimization over a large space of possible groupings from simultaneously grouped and recognized sketched shapes. The optimization utilizes a classifier that assigns a class label to a collection of strokes. The overall grouping optimization assumes the properties of the classifier so that if the classifier is scale and rotation invariant the optimization will be as well. Instances of the present invention employ a variant of AdaBoost to facilitate in recognizing/classifying symbols. Instances of the present invention employ dynamic programming and/or A-star search to perform optimization. The present invention applies to both hand-sketched shapes and printed handwritten text, and even heterogeneous mixtures of the two.
    • 本发明利用空间关系来提供识别文本和/或图形的系统手段。 这允许以其符号意义来增加草图形状,实现许多功能,包括智能编辑,美化和视觉语言的交互式模拟。 空间识别方法从同时分组和识别的草图形状的可能分组的大空间中获得基于搜索的优化。 优化利用了将类标签分配给笔画集合的分类器。 整体分组优化假设分类器的属性,以便如果分类器是缩放和旋转不变量,则优化将同样如此。 本发明的实施例采用AdaBoost的变体来促进识别/分类符号。 本发明的实施例采用动态规划和/或A星搜索来执行优化。 本发明适用于手绘形状和印刷手写文本,甚至适用于两者的异构混合物。
    • 3. 发明授权
    • Application of grammatical parsing to visual recognition tasks
    • 语法解析在视觉识别任务中的应用
    • US07639881B2
    • 2009-12-29
    • US11151708
    • 2005-06-13
    • Paul A. ViolaMichael Shilman
    • Paul A. ViolaMichael Shilman
    • G06K9/00G06K9/34G06K9/62G06K9/72
    • G06K9/726G06F17/271G06K2209/01
    • Image recognition is utilized to facilitate in scoring parse trees for two-dimensional recognition tasks. Trees and subtrees are rendered as images and then utilized to determine parsing scores. Other instances of the subject invention can incorporate additional features such as stroke curvature and/or nearby white space as rendered images as well. Geometric constraints can also be employed to increase performance of a parsing process, substantially improving parsing speed, some even resolvable in polynomial time. Additional performance enhancements can be achieved in yet other instances of the subject invention by employing constellations of integral images and/or integral images of document features.
    • 图像识别用于方便得分解树进行二维识别任务。 树和子树被渲染为图像,然后用于确定解析分数。 本发明的其它实例可以将诸如笔画曲率和/或附近的空白区域的附加特征也作为渲染图像。 也可以采用几何约束来提高解析过程的性能,大大提高解析速度,甚至可以在多项式时间内解析。 通过使用整体图像的星座和/或文档特征的整体图像,可以在本发明的其它实例中实现附加的性能增强。
    • 4. 发明申请
    • Image Organization
    • 图像组织
    • US20080226174A1
    • 2008-09-18
    • US11725129
    • 2007-03-15
    • Gang HuaSteven M. DruckerMichael RevowPaul A. ViolaRichard Zemel
    • Gang HuaSteven M. DruckerMichael RevowPaul A. ViolaRichard Zemel
    • G06K9/68G06K9/46
    • G06K9/00228G06K9/6251
    • A system for organizing images includes an extraction component that extracts visual information (e.g., faces, scenes, etc.) from the images. The extracted visual information is provided to a comparison component which computes similarity confidence data between the extracted visual information. The similarity confidence data is an indication of the likelihood that items of extracted visual information are similar. The comparison component then generates a visual distribution of the extracted visual information based upon the similarity confidence data. The visual distribution can include groupings of the extracted visual information based on computed similarity confidence data. For example, the visual distribution can be a two-dimensional layout of faces organized based on the computed similarity confidence data—with faces in closer proximity faces computed to have a greater probability of representing the same person. The visual distribution can then be utilized by a user to sort, organize and/or tag images.
    • 用于组织图像的系统包括从图像中提取视觉信息(例如,面部,场景等)的提取组件。 提取的视觉信息被提供给计算提取的视觉信息之间的相似性置信度数据的比较部件。 相似性置信度数据是提取的视觉信息的项目相似的可能性的指示。 然后,比较组件基于相似性置信度数据生成所提取的视觉信息的视觉分布。 视觉分布可以包括基于计算的相似性置信度数据提取的视觉信息的分组。 例如,视觉分布可以是基于所计算的相似性置信度数据组织的面部的二维布局,其中更接近的面中的面被计算为具有更大的代表同一人的概率。 然后用户可以利用视觉分布来对图像进行分类,组织和/或标记。
    • 6. 发明授权
    • Method and system for providing an audio element cache in a customized personal radio broadcast
    • 用于在定制的个人无线电广播中提供音频元素高速缓存的方法和系统
    • US06985694B1
    • 2006-01-10
    • US09656884
    • 2000-09-07
    • Jeremy S. De BonetPaul A. Viola
    • Jeremy S. De BonetPaul A. Viola
    • H04H1/00
    • H04H20/40H04H60/66
    • An audio element cache is provided that is capable of caching audio elements for each user in a personal radio server system. In operation, customized radio content is provided to remote listeners in a personal radio server system by: storing a plurality of audio elements in a file server; retrieving a subset of the plurality of audio elements from the file server by predicting the content desired by a remote listener based on a user profile of the remote listener; storing the subset of the plurality of audio elements in an audio element cache; selecting audio elements to provide to a remote listener from the audio element cache; and transmitting the audio elements to the remote listener. In an embodiment, the plurality of audio elements are stored in the audio element cache when a remote listener logs-on the personal radio server system.
    • 提供音频元素高速缓存,其能够在个人无线电服务器系统中缓存每个用户的音频元素。 在操作中,通过以下方式将定制的无线电内容提供给个人无线电服务器系统中的远程收听者:将多个音频元素存储在文件服务器中; 基于所述远程侦听器的用户简档,通过预测远程侦听器所期望的内容来从所述文件服务器检索所述多个音频元素的子集; 将所述多个音频元素的子集存储在音频元素高速缓存中; 选择音频元素以从音频元素高速缓存提供给远程收听者; 并将音频元素发送到远程收听者。 在一个实施例中,当远程侦听器登录在个人无线电服务器系统上时,多个音频元素被存储在音频元素高速缓存中。
    • 8. 发明授权
    • Grammatical parsing of document visual structures
    • 文字视觉结构的语法解析
    • US08249344B2
    • 2012-08-21
    • US11173280
    • 2005-07-01
    • Paul A. ViolaMichael Shilman
    • Paul A. ViolaMichael Shilman
    • G06K9/34G06K9/72
    • G06K9/726G06F17/271G06K2209/01
    • A two-dimensional representation of a document is leveraged to extract a hierarchical structure that facilitates recognition of the document. The visual structure is grammatically parsed utilizing two-dimensional adaptations of statistical parsing algorithms. This allows recognition of layout structures (e.g., columns, authors, titles, footnotes, etc.) and the like such that structural components of the document can be accurately interpreted. Additional techniques can also be employed to facilitate document layout recognition. For example, grammatical parsing techniques that utilize machine learning, parse scoring based on image representations, boosting techniques, and/or “fast features” and the like can be employed to facilitate in document recognition.
    • 利用文档的二维表示来提取便于识别文档的层次结构。 使用统计解析算法的二维适应来语法解析视觉结构。 这允许识别布局结构(例如,列,作者,标题,脚注等)等,使得可以准确地解释文档的结构组件。 还可以采用附加技术来促进文档布局识别。 例如,可以采用利用机器学习,基于图像表示的分析评分,增强技术和/或“快速特征”等的语法解析技术,以促进文档识别。
    • 9. 发明授权
    • Face recognition using discriminatively trained orthogonal tensor projections
    • 使用区分训练正交张量投影的人脸识别
    • US07936906B2
    • 2011-05-03
    • US11763909
    • 2007-06-15
    • Gang HuaPaul A ViolaSteven M. DruckerMichael Revow
    • Gang HuaPaul A ViolaSteven M. DruckerMichael Revow
    • G06K9/00
    • G06K9/00288G06K9/6232
    • Systems and methods are described for face recognition using discriminatively trained orthogonal rank one tensor projections. In an exemplary system, images are treated as tensors, rather than as conventional vectors of pixels. During runtime, the system designs visual features—embodied as tensor projections—that minimize intraclass differences between instances of the same face while maximizing interclass differences between the face and faces of different people. Tensor projections are pursued sequentially over a training set of images and take the form of a rank one tensor, i.e., the outer product of a set of vectors. An exemplary technique ensures that the tensor projections are orthogonal to one another, thereby increasing ability to generalize and discriminate image features over conventional techniques. Orthogonality among tensor projections is maintained by iteratively solving an ortho-constrained eigenvalue problem in one dimension of a tensor while solving unconstrained eigenvalue problems in additional dimensions of the tensor.
    • 使用区分训练的正交秩一张量投影描述用于人脸识别的系统和方法。 在示例性系统中,图像被视为张量,而不是像传统的像素矢量。 在运行期间,系统设计视觉特征 - 体现为张量投影 - 最大限度地减少不同人脸部和脸部之间的类间差异,从而最大限度地减少同一脸部实例之间的差异。 张量投影在训练图像集上顺序追溯,并采取一级张量的形式,即一组向量的外积。 示例性技术确保张量投影彼此正交,从而增加了与常规技术相比的概括和区分图像特征的能力。 通过迭代求解张量的一维中的邻域约束特征值问题,同时解决张量的附加维度中的无约束特征值问题,维持张量投影中的正交性。