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公开(公告)号：US20130028508A1
公开(公告)日：2013-01-31
申请号：US13190753
申请日：2011-07-26
IPC分类号： G06K9/62
CPC分类号： G06K9/00476
摘要： A system and method for computing a place profile are disclosed. The method includes providing a geographical definition of a place, retrieving a set of images based on the geographical place definition. With a classifier, image-level statistics for the retrieved images are generated. The classifier has been trained to generate image-level statistics for a finite set of classes, such as different activities. The image-level statistics are aggregated to generate a place profile for the defined place which may be displayed to a user who has provided information for generating the geographical definition or used in an application such as a recommender system or to generate a personal profile for the user.
摘要翻译： 公开了一种用于计算地点轮廓的系统和方法。 该方法包括提供地点的地理定义，基于地理位置定义检索一组图像。 使用分类器，生成检索到的图像的图像级别统计信息。 已经对分类器进行了训练，以生成有限集合类（例如不同活动）的图像级统计信息。 聚集图像级统计信息以生成可以向已经提供用于生成地理定义的信息的用户显示的定义的地点的位置简档，或者在诸如推荐器系统之类的应用中使用的位置简档，或者为 用户。
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公开(公告)号：US09298982B2
公开(公告)日：2016-03-29
申请号：US13190753
申请日：2011-07-26
IPC分类号： G06K9/00
CPC分类号： G06K9/00476
摘要： A system and method for computing a place profile are disclosed. The method includes providing a geographical definition of a place, retrieving a set of images based on the geographical place definition. With a classifier, image-level statistics for the retrieved images are generated. The classifier has been trained to generate image-level statistics for a finite set of classes, such as different activities. The image-level statistics are aggregated to generate a place profile for the defined place which may be displayed to a user who has provided information for generating the geographical definition or used in an application such as a recommender system or to generate a personal profile for the user.
摘要翻译： 公开了一种用于计算地点轮廓的系统和方法。 该方法包括提供地点的地理定义，基于地理位置定义检索一组图像。 使用分类器，生成检索到的图像的图像级统计信息。 已经对分类器进行了训练，以生成有限集合类（例如不同活动）的图像级统计信息。 聚集图像级统计信息以生成可以向已经提供用于生成地理定义的信息的用户显示的定义的地点的位置简档，或者在诸如推荐器系统之类的应用中使用的位置简档，或者为 用户。
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公开(公告)号：US20130060786A1
公开(公告)日：2013-03-07
申请号：US13224373
申请日：2011-09-02
IPC分类号： G06F17/30
CPC分类号： G06F17/30256 , G06F17/30265 , G06F17/30277 , G06K9/3258 , G06K9/4676 , G06K9/6277 , G06K2209/01 , G06K2209/15
摘要： A method and system are disclosed for conducting text-based searches of images using a visual signature associated with each image. A measure of string similarity between a query and an annotation associated with each entry in a first database is computed, and based upon the computed string similarity measures, a set of entries from the first database is selected. Each entry of the first database also includes an associated visual signature. At least one entry is then retrieved from a second database based upon a measure of visual similarity between a visual signature of each of the entries in the second database and the visual signatures of the entries in the selected set. Information corresponding to the retrieved entries from the second database is then generated.
摘要翻译： 公开了一种用于使用与每个图像相关联的视觉签名进行基于图像的基于文本的搜索的方法和系统。 计算查询和与第一数据库中的每个条目相关联的注释之间的字符串相似度的度量，并且基于所计算的字符串相似性度量，选择来自第一数据库的一组条目。 第一数据库的每个条目还包括相关联的视觉签名。 基于第二数据库中的每个条目的视觉签名与所选集合中的条目的视觉签名之间的视觉相似度的度量，从第二数据库检索至少一个条目。 然后生成与从第二数据库检索到的条目相对应的信息。
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4.发明授权Methods and systems for improved license plate signature matching by similarity learning on synthetic images 有权通过合成图像上的相似性学习改进车牌签名匹配的方法和系统公开(公告)号：US08588470B2
公开(公告)日：2013-11-19
申请号：US13300124
申请日：2011-11-18
申请人： Jose Antonio Rodriguez Serrano , Raja Bala , Florent Perronnin , Craig John Saunders , Yonghui Zhao
发明人： Jose Antonio Rodriguez Serrano , Raja Bala , Florent Perronnin , Craig John Saunders , Yonghui Zhao
IPC分类号： G06K9/00
CPC分类号： G06K9/6255 , G06K9/6217 , G06K2209/15
摘要： Methods and systems for improved license plate signature matching by similarity learning on synthetic images comprise generating a plurality of synthetic license plate images; applying one or more transformations to the synthetic license plate images to cause the synthetic license plate images to more closely resemble authentic license plate image captures; and providing the synthetic license plate images as inputs to a machine distance learning algorithm in which weighted similarity scores are calculated between signatures of analogous and non-analogous license plate images and one or more sets of signature weights are iteratively adjusted to increase the likelihood that comparing analogous license plate images results in high weighted signature similarity scores and comparing non-analogous license plate images results in low weighted signature similarity scores.
摘要翻译： 用于通过合成图像上的相似性学习改进车牌签名匹配的方法和系统包括生成多个合成车牌图像; 对合成车牌图像应用一个或多个变换，使得合成车牌图像更接近真实的车牌图像捕获; 并且将合成车牌图像作为输入提供给机器距离学习算法，其中在类似和非类似车牌图像的签名与一组或多组签名权重之间计算加权相似性分数，以迭代地调整比较的可能性 类似的车牌图像导致高加权签名相似性得分，并且比较非类似车牌图像导致低加权签名相似性得分。
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公开(公告)号：US08533204B2
公开(公告)日：2013-09-10
申请号：US13224373
申请日：2011-09-02
IPC分类号： G06F7/00
CPC分类号： G06F17/30256 , G06F17/30265 , G06F17/30277 , G06K9/3258 , G06K9/4676 , G06K9/6277 , G06K2209/01 , G06K2209/15
摘要： A method and system are disclosed for conducting text-based searches of images using a visual signature associated with each image. A measure of string similarity between a query and an annotation associated with each entry in a first database is computed, and based upon the computed string similarity measures, a set of entries from the first database is selected. Each entry of the first database also includes an associated visual signature. At least one entry is then retrieved from a second database based upon a measure of visual similarity between a visual signature of each of the entries in the second database and the visual signatures of the entries in the selected set. Information corresponding to the retrieved entries from the second database is then generated.
摘要翻译： 公开了一种用于使用与每个图像相关联的视觉签名进行基于图像的基于文本的搜索的方法和系统。 计算查询和与第一数据库中的每个条目相关联的注释之间的字符串相似度的度量，并且基于所计算的字符串相似性度量，选择来自第一数据库的一组条目。 第一数据库的每个条目还包括相关联的视觉签名。 基于第二数据库中的每个条目的视觉签名与所选集合中的条目的视觉签名之间的视觉相似度的度量，从第二数据库检索至少一个条目。 然后生成与从第二数据库检索到的条目相对应的信息。
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公开(公告)号：US20130290222A1
公开(公告)日：2013-10-31
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：US08326087B2
公开(公告)日：2012-12-04
申请号：US12277779
申请日：2008-11-25
CPC分类号： G06K9/00758 , G06F17/30247 , G06F17/30265 , G06F17/30781
摘要： As set forth herein, a computer-based method is employed to align a sequences of images. Metadata associated with images from two or more sources is received and a time stamp is extracted from the metadata. The images are sorted into sequences based at least in part upon the image source. The similarity of images from disparate sequences is measured and image pairs from disparate sequences with a similarity greater than a predetermined threshold are identified. A sequence of images is aligned by minimizing the misalignment of pairs.
摘要翻译： 如本文所述，采用基于计算机的方法来对准图像序列。 接收与来自两个或更多个源的图像相关联的元数据，并从元数据中提取时间戳。 至少部分地基于图像源将图像分类成序列。 测量来自不同序列的图像的相似性，并且识别具有大于预定阈值的相似性的不同序列的图像对。 通过最小化对的不对准来对齐一系列图像。
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8.发明授权System and method for object class localization and semantic class based image segmentation 有权用于对象类定位和基于语义类的图像分割的系统和方法公开(公告)号：US08111923B2
公开(公告)日：2012-02-07
申请号：US12191579
申请日：2008-08-14
申请人： Gabriela Csurka , Florent Perronnin
发明人： Gabriela Csurka , Florent Perronnin
CPC分类号： G06K9/00624 , G06K9/342 , G06K9/4676 , G06T7/11 , G06T2207/10024 , G06T2207/20021 , G06T2207/30236 , G06T2207/30252
摘要： An automated image processing system and method are provided for class-based segmentation of a digital image. The method includes extracting a plurality of patches of an input image. For each patch, at least one feature is extracted. The feature may be a high level feature which is derived from the application of a generative model to a representation of low level feature(s) of the patch. For each patch, and for at least one object class from a set of object classes, a relevance score for the patch, based on the at least one feature, is computed. For at least some or all of the pixels of the image, a relevance score for the at least one object class based on the patch scores is computed. An object class is assigned to each of the pixels based on the computed relevance score for the at least one object class, allowing the image to be segmented and the segments labeled, based on object class.
摘要翻译： 提供了一种用于数字图像的基于分类的分割的自动图像处理系统和方法。 该方法包括提取输入图像的多个片段。 对于每个补丁，至少提取一个要素。 该特征可以是从生成模型的应用导出到补丁的低级特征的表示的高级特征。 对于每个补丁以及来自一组对象类的至少一个对象类，基于至少一个特征来计算补丁的相关性得分。 对于图像的至少一些或全部像素，计算基于补丁得分的至少一个对象类别的相关度得分。 基于所计算的至少一个对象类的相关性分数，将对象类分配给每个像素，允许根据对象类来分割图像和标记的图像。
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9.发明申请FAST ALGORITHM FOR CONVEX OPTIMIZATION WITH APPLICATION TO DENSITY ESTIMATION AND CLUSTERING 有权用于突变优化的快速算法应用于密度估计和聚类公开(公告)号：US20100088073A1
公开(公告)日：2010-04-08
申请号：US12245939
申请日：2008-10-06
IPC分类号： G06F17/10
CPC分类号： G06F17/11 , G06K9/6222 , G06K9/6226
摘要： A method of maximizing a concave log-likelihood function comprises: selecting a pair of parameters from a plurality of adjustable parameters of a concave log-likelihood function; maximizing a value of the concave log-likelihood function respective to an adjustment value to generate an optimal adjustment value, wherein the value of one member of the selected pair of parameters is increased by the adjustment value and the value of the other member of the selected pair of parameters is decreased by the adjustment value; updating values of the plurality of adjustable parameters by increasing the value of the one member of the selected pair of parameters by the optimized adjustment value and decreasing the value of the other member of the selected pair of parameters by the optimized adjustment value; and repeating the selecting, maximizing, and updating for different pairs of parameters to identify optimized values of the plurality of adjustable parameters.
摘要翻译： 最大化凹对数似然函数的方法包括：从凹对数似然函数的多个可调参数中选择一对参数; 最大化相应于调整值的凹对数似然函数的值以生成最佳调整值，其中所选择的一对参数中的一个成员的值被增加了所选择的另一成员的调整值和值 一对参数减少调整值; 通过优化的调整值增加所选择的一对参数中的一个成员的值并通过优化的调整值减小所选择的一对参数中的另一个成员的值来更新多个可调参数的值; 以及重复对不同参数对的选择，最大化和更新以识别所述多个可调参数的优化值。
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公开(公告)号：US20090271433A1
公开(公告)日：2009-10-29
申请号：US12109496
申请日：2008-04-25
IPC分类号： G06F17/30
CPC分类号： G06F17/16 , G06K9/6224
摘要： Object clustering techniques are disclosed. A nonnegative sparse similarity matrix is constructed for a set of objects. Nonnegative factorization of the nonnegative sparse similarity matrix is performed. Objects of the set of objects are allocated to clusters based on factor matrices generated by the nonnegative factorization of the nonnegative sparse similarity matrix.
摘要翻译： 公开了对象聚类技术。 为一组对象构建非负稀疏相似矩阵。 执行非负稀疏相似矩阵的非负因子分解。 基于由非负稀疏相似矩阵的非负因子分解产生的因子矩阵将该组对象的对象分配给群集。
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