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41.发明授权Integration of content-based relevant information into print jobs and applications using same 有权将基于内容的相关信息集成到打印作业和使用它们的应用程序中公开(公告)号：US07729001B2
公开(公告)日：2010-06-01
申请号：US11635204
申请日：2006-12-07
申请人： Florent Perronnin
发明人： Florent Perronnin
CPC分类号： G06Q30/02
摘要： In a printing method, summarizing information is extracted from a print job. Additional content is generated based on the summarizing information. The additional content is integrated into the print job to produce an augmented print job including the additional content. The augmented print job is printed. In an illustrative advertising application, summarizing information is extracted from a print job, advertising content is selected from a database of advertising content based on the summarizing information, and the selected advertising content is integrated into the print job.
摘要翻译： 在打印方法中，从打印作业中提取汇总信息。 基于总结信息生成附加内容。 附加内容被集成到打印作业中以产生包括附加内容的增强打印作业。 打印增加的打印作业。 在说明性广告应用中，从打印作业提取总结信息，基于总结信息从广告内容的数据库中选择广告内容，并且将所选择的广告内容集成到打印作业中。
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42.发明申请公开(公告)号：US20080069456A1
公开(公告)日：2008-03-20
申请号：US11524100
申请日：2006-09-19
申请人： Florent Perronnin
发明人： Florent Perronnin
CPC分类号： G06K9/6267 , G06K9/4671 , G06K9/4676
摘要： Category context models (64) and a universal context model (62) are generated including sums of soft co-occurrences of pairs of visual words in geometric proximity to each other in training images (50) assigned to each category and assigned to all categories, respectively. Context information (76) about an image to be classified (70) are generated including sums of soft co-occurrences of pairs of visual words in geometric proximity to each other in the image to be classified. For each category (82), a comparison is made of (i) closeness of the context information about the image to be classified with the corresponding category context model and (ii) closeness of the context information about the image to be classified with the universal context model. An image category (92) is assigned to the image to be classified being based on the comparisons.
摘要翻译： 产生类别上下文模型（64）和通用上下文模型（62），包括在分配给每个类别并分配给所有类别的训练图像（50）中彼此几何接近的视觉对对的软对共和的和， 分别。 生成关于要分类的图像（70）的上下文信息（76），包括在要分类的图像中彼此几何接近的视觉对的双对的软合并的和。 对于每个类别（82），比较（i）关于要分类的图像的上下文信息与相应的类别上下文模型的接近度，以及（ii）关于将被分类为通用的图像的上下文信息的接近度 上下文模型。 基于比较将图像类别（92）分配给要分类的图像。
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公开(公告)号：US06970820B2
公开(公告)日：2005-11-29
申请号：US09792928
申请日：2001-02-26
CPC分类号： G10L13/04 , G10L2021/0135
摘要： The speech synthesizer is personalized to sound like or mimic the speech characteristics of an individual speaker. The individual speaker provides a quantity of enrollment data, which can be extracted from a short quantity of speech, and the system modifies the base synthesis parameters to more closely resemble those of the new speaker. More specifically, the synthesis parameters may be decomposed into speaker dependent parameters, such as context-independent parameters, and speaker independent parameters, such as context dependent parameters. The speaker dependent parameters are adapted using enrollment data from the new speaker. After adaptation, the speaker dependent parameters are combined with the speaker independent parameters to provide a set of personalized synthesis parameters. To adapt the parameters with a small amount of enrollment data, an eigenspace is constructed and used to constrain the position of the new speaker so that context independent parameters not provided by the new speaker may be estimated.
摘要翻译： 语音合成器被个性化以发音或模仿单个扬声器的语音特征。 单个扬声器提供一定数量的登记数据，其可以从短语言中提取，并且系统将基本合成参数修改为更接近于新说话者的参考数据。 更具体地，合成参数可以被分解为与扬声器相关的参数，诸如与上下文无关的参数，以及与扬声器无关的参数，诸如与上下文相关的参数。 使用来自新扬声器的注册数据来调整与扬声器相关的参数。 在适应之后，将扬声器依赖参数与扬声器独立参数组合以提供一组个性化合成参数。 为了使参数具有少量的注册数据，构造本征空间并用于约束新的说话者的位置，以便可以估计不能由新发言者提供的上下文独立参数。
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公开(公告)号：US09075824B2
公开(公告)日：2015-07-07
申请号：US13458183
申请日：2012-04-27
CPC分类号： G06F17/30247 , G06K9/6247 , G06K9/6259
摘要： An instance-level retrieval method and system are provided. A representation of a query image is embedded in a multi-dimensional space using a learned projection. The projection is learned using category-labeled training data to optimize a classification rate on the training data. The joint learning of the projection and the classifiers improves the computation of similarity/distance between images by embedding them in a subspace where the similarity computation outputs more accurate results. An input query image can thus be used to retrieve similar instances in a database by computing the comparison measure in the embedding space.
摘要翻译： 提供实例级检索方法和系统。 使用学习投影将查询图像的表示嵌入到多维空间中。 使用类别标记的训练数据学习投影，以优化训练数据的分类率。 投影和分类器的联合学习通过将图像嵌入到相似度计算输出更准确的结果的子空间来改善图像之间的相似度/距离的计算。 因此，输入查询图像可以用于通过计算嵌入空间中的比较度量来检索数据库中的类似实例。
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公开(公告)号：US08725059B2
公开(公告)日：2014-05-13
申请号：US12771534
申请日：2010-04-30
IPC分类号： G09B3/00
CPC分类号： G06Q10/10
摘要： An educational recommender system and a method for recommending an educational game to be used by a group of at least two students are provided. The method includes receiving a request to recommend an educational game to use with the group of students, and accessing student data relating to the at least two students including granular assessment data. The granular assessment data includes a result of at least one assessment administered to respective students, wherein each assessment includes a plurality of problems for assessing at least one of the students and the associated result includes an independent evaluation of each respective problem. The method further includes selecting an educational game that exercises the students in an academic area, including selecting the level of the academic area exercised based on granular assessment data associated with each of the respective students.
摘要翻译： 提供一种教育推荐系统和一种用于推荐由一组至少两名学生使用的教育游戏的方法。 该方法包括接收推荐与该组学生一起使用的教育游戏的请求，以及访问与至少两个学生相关的学生数据，包括粒度评估数据。 粒度评估数据包括对相应学生进行至少一次评估的结果，其中每个评估包括用于评估至少一个学生和相关结果的多个问题包括对每个相应问题的独立评估。 该方法还包括选择在学术领域中练习学生的教育游戏，包括根据与每个学生相关联的粒度评估数据选择所执行的学术领域的水平。
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公开(公告)号：US08699939B2
公开(公告)日：2014-04-15
申请号：US12339979
申请日：2008-12-19
申请人： Kristine A. German , Robert M. Lofthus , Robert Roy Price , Florent Perronnin , Claudio Cifarelli , Minh Do , Rong Zhou
发明人： Kristine A. German , Robert M. Lofthus , Robert Roy Price , Florent Perronnin , Claudio Cifarelli , Minh Do , Rong Zhou
IPC分类号： G09B3/00
CPC分类号： G06Q10/10
摘要： An educational recommender system and a method are provided. The method includes receiving a request to recommend a course of action related to a plurality of current students; accessing a computer database storing student data that corresponds to the plurality of current students; clustering in a computer process the plurality of current students into at least two clusters based at least on granular assessment data associated with student data corresponding to respective current students; and outputting the results of the clustering to a user. The granular assessment data includes a result of an assessment administered to respective students of the plurality of current students, and each assessment includes a plurality of questions for assessing one of the current students. The associated result includes an independent evaluation of each respective question of the plurality of questions.
摘要翻译： 提供教育推荐系统和方法。 该方法包括接收关于推荐与多个当前学生相关的行动过程的请求; 访问存储对应于多个当前学生的学生数据的计算机数据库; 至少基于与对应于当前学生的学生数据相关联的粒度评估数据，将计算机中的多个群集进行处理，将多个当前学生进入至少两个群集; 并将聚类的结果输出给用户。 粒度评估数据包括对多名当前学生的各个学生进行评估的结果，并且每个评估包括用于评估当前学生之一的多个问题。 相关联的结果包括对各个问题的每个相应问题的独立评估。
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公开(公告)号：US08532399B2
公开(公告)日：2013-09-10
申请号：US12859898
申请日：2010-08-20
申请人： Florent Perronnin , Jorge Sanchez , Thomas Mensink
发明人： Florent Perronnin , Jorge Sanchez , Thomas Mensink
IPC分类号： G06K9/00
CPC分类号： G06K9/6234 , G06K9/6249
摘要： An input image representation is generated based on an aggregation of local descriptors extracted from an input image, and is adjusted by performing a power normalization, an Lp normalization such as an L2 normalization, or both. In some embodiments the generating comprises modeling the extracted local descriptors using a probabilistic model to generate the input image representation comprising probabilistic model component values for a set of probabilistic model components. In some such embodiments the probabilistic model comprises a Gaussian mixture model and the probabilistic model components comprise Gaussian components of the Gaussian mixture model. The generating may include partitioning the input image into a plurality of image partitions using a spatial pyramids partitioning model, extracting local descriptors, such as Fisher vectors, from the image partitions, and concatenating the local descriptors extracted from the image partitions.
摘要翻译： 基于从输入图像提取的局部描述符的聚合生成输入图像表示，并且通过执行功率归一化，Lp归一化（诸如L2归一化）或两者来进行调整。 在一些实施例中，生成包括使用概率模型对所提取的局部描述符进行建模，以生成包括用于一组概率模型分量的概率模型分量值的输入图像表示。 在一些这样的实施例中，概率模型包括高斯混合模型，概率模型分量包括高斯混合模型的高斯分量。 生成可以包括使用空间金字塔分割模型将输入图像划分成多个图像分区，从图像分区中提取诸如Fisher向量的局部描述符，以及连接从图像分区提取的局部描述符。
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48.发明授权Photography assistant and method for assisting a user in photographing landmarks and scenes 有权摄影助手和辅助用户拍摄地标和场景的方法公开(公告)号：US08332429B2
公开(公告)日：2012-12-11
申请号：US12820647
申请日：2010-06-22
IPC分类号： G06F7/00
CPC分类号： G06F17/30277 , G06F17/30241 , G06F17/30265 , G06F17/30268 , H04N1/00183 , H04N5/23222
摘要： A method and system to help photographers to take better quality pictures of landmarks and scenes are disclosed. A user is guided with examples of existing quality images, which are extracted from a database, of the same or similar landmarks or scenes. The method includes taking a query photograph that may include an image associated with a GPS location and other metadata, and using information extracted from the image to retrieve existing, similar images. The images retrieved may be ordered according to different criteria. When a user selects one as a model image, the user is provided with assistance for taking a target photograph of similar quality.
摘要翻译： 公开了一种帮助摄影师拍摄更好的地标和场景照片的方法和系统。 使用者从相同或相似的地标或场景的数据库提取的现有质量图像的示例引导。 该方法包括拍摄可以包括与GPS位置和其他元数据相关联的图像的查询照片，以及使用从图像提取的信息来检索现有的相似图像。 检索的图像可以根据不同的标准进行排序。 当用户选择一个作为模型图像时，向用户提供用于拍摄类似质量的目标照片的帮助。
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49.发明授权Fast and efficient nonlinear classifier generated from a trained linear classifier 有权从训练有素的线性分类器生成的快速高效的非线性分类器公开(公告)号：US08280828B2
公开(公告)日：2012-10-02
申请号：US12483391
申请日：2009-06-12
申请人： Florent Perronnin , Jorge Sanchez
发明人： Florent Perronnin , Jorge Sanchez
CPC分类号： G06K9/6271 , G06N99/005
摘要： A classifier method comprises: projecting a set of training vectors in a vector space to a comparison space defined by a set of reference vectors using a comparison function to generate a corresponding set of projected training vectors in the comparison space; training a linear classifier on the set of projected training vectors to generate a trained linear classifier operative in the comparison space; and transforming the trained linear classifier operative in the comparison space into a trained nonlinear classifier that is operative in the vector space to classify an input vector.
摘要翻译： 分类器方法包括：使用比较函数将矢量空间中的一组训练矢量投影到由一组参考矢量定义的比较空间，以在比较空间中生成相应的一组投影训练矢量; 在所述一组投影训练矢量上训练线性分类器以产生在比较空间中操作的经训练的线性分类器; 以及将在所述比较空间中操作的经训练的线性分类器变换成在所述向量空间中操作以对输入向量进行分类的经训练的非线性分类器。
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公开(公告)号：US20120143853A1
公开(公告)日：2012-06-07
申请号：US12960018
申请日：2010-12-03
申请人： Albert Gordo , Florent Perronnin
发明人： Albert Gordo , Florent Perronnin
IPC分类号： G06F17/30
CPC分类号： G06F17/30247
摘要： A system and method for comparing a query object and one or more of a set of database objects are provided. The method includes providing quantized representations of database objects. The database objects have each been transformed with a quantized embedding function which is the composition of a real-valued embedding function and a quantization function. The query object is transformed to a representation of the query object in a real-valued embedding space using the real-valued embedding function. Query-dependent estimated distance values are computed for the query object, based on the transformed query object and stored. A comparison (e.g., distance or similarity) measure between the query object and each of the quantized database object representations is computed based on the stored query-dependent estimated distance values. Data is output based on the comparison computation.
摘要翻译： 提供了一种用于比较查询对象与一组数据库对象中的一个或多个的系统和方法。 该方法包括提供数据库对象的量化表示。 数据库对象每个都已经用量化嵌入函数进行了变换，该嵌入函数是实值嵌入函数和量化函数的组合。 使用实值嵌入函数将查询对象转换为实值嵌入空间中的查询对象的表示。 基于所转换的查询对象并存储查询对象，计算与查询相关的估计距离值。 基于存储的查询相关估计距离值来计算查询对象和每个量化数据库对象表示之间的比较（例如距离或相似度）度量。 基于比较计算输出数据。
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