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公开(公告)号：US07519201B2
公开(公告)日：2009-04-14
申请号：US11553388
申请日：2006-10-26
CPC分类号： G06K9/4647 , G06K9/00369
摘要： A method and system efficiently and accurately detects humans in a test image and classifies their pose. In a training stage, a probabilistic model is derived in an unsupervised or semi-supervised manner such that at least some poses are not manually labeled. The model provides two sets of model parameters to describe the statistics of images containing humans and images of background scenes. In a testing stage, the probabilistic model is used to determine if a human is present in the image, and classify the human's pose based on the poses in the training images. A solution is efficiently provided to both human detection and pose classification by using the same probabilistic model to solve the problems.
摘要翻译： 一种方法和系统有效和准确地检测测试图像中的人类并对其姿态进行分类。 在训练阶段，以无监督或半监督的方式导出概率模型，使得至少一些姿势不是手动标记的。 该模型提供两组模型参数来描述包含人类和背景场景图像的图像的统计。 在测试阶段，概率模型用于确定人物是否存在于图像中，并且基于训练图像中的姿态对人的姿势进行分类。 通过使用相同的概率模型来解决问题，有效地提供了人类检测和姿态分类的解决方案。
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2.发明授权Fast human pose estimation using appearance and motion via multi-dimensional boosting regression 有权通过多维加速回归，使用外观和运动的快速人体姿态估计公开(公告)号：US07778446B2
公开(公告)日：2010-08-17
申请号：US11950662
申请日：2007-12-05
IPC分类号： G06K9/00
CPC分类号： G06K9/00342 , G06K9/6257
摘要： Methods and systems are described for three-dimensional pose estimation. A training module determines a mapping function between a training image sequence and pose representations of a subject in the training image sequence. The training image sequence is represented by a set of appearance and motion patches. A set of filters are applied to the appearance and motion patches to extract features of the training images. Based on the extracted features, the training module learns a multidimensional mapping function that maps the motion and appearance patches to the pose representations of the subject. A testing module outputs a fast human pose estimation by applying the learned mapping function to a test image sequence.
摘要翻译： 描述了用于三维姿态估计的方法和系统。 训练模块确定训练图像序列和训练图像序列中的对象的姿态表示之间的映射函数。 训练图像序列由一组外观和运动补丁表示。 将一组滤镜应用于外观和运动补片以提取训练图像的特征。 基于提取的特征，训练模块学习将运动和外观补片映射到对象的姿态表示的多维映射函数。 测试模块通过将学习的映射函数应用于测试图像序列来输出快速人体姿态估计。
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公开(公告)号：US20070098254A1
公开(公告)日：2007-05-03
申请号：US11553388
申请日：2006-10-26
CPC分类号： G06K9/4647 , G06K9/00369
摘要： A method and system efficiently and accurately detects humans in a test image and classifies their pose. In a training stage, a probabilistic model is derived in an unsupervised or semi-supervised manner such that at least some poses are not manually labeled. The model provides two sets of model parameters to describe the statistics of images containing humans and images of background scenes. In a testing stage, the probabilistic model is used to determine if a human is present in the image, and classify the human's pose based on the poses in the training images. A solution is efficiently provided to both human detection and pose classification by using the same probabilistic model to solve the problems.
摘要翻译： 一种方法和系统有效和准确地检测测试图像中的人类并对其姿态进行分类。 在训练阶段，以无监督或半监督的方式导出概率模型，使得至少一些姿势不是手动标记的。 该模型提供两组模型参数来描述包含人类和背景场景图像的图像的统计。 在测试阶段，概率模型用于确定人物是否存在于图像中，并且基于训练图像中的姿态对人的姿势进行分类。 通过使用相同的概率模型来解决问题，有效地提供了人类检测和姿态分类的解决方案。
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4.发明申请Fast Human Pose Estimation Using Appearance And Motion Via Multi-Dimensional Boosting Regression 有权通过多维增强回归的外观和运动的快速人体姿态估计公开(公告)号：US20080137956A1
公开(公告)日：2008-06-12
申请号：US11950662
申请日：2007-12-05
IPC分类号： G06K9/00
CPC分类号： G06K9/00342 , G06K9/6257
摘要： Methods and systems are described for three-dimensional pose estimation. A training module determines a mapping function between a training image sequence and pose representations of a subject in the training image sequence. The training image sequence is represented by a set of appearance and motion patches. A set of filters are applied to the appearance and motion patches to extract features of the training images. Based on the extracted features, the training module learns a multidimensional mapping function that maps the motion and appearance patches to the pose representations of the subject. A testing module outputs a fast human pose estimation by applying the learned mapping function to a test image sequence.
摘要翻译： 描述了用于三维姿态估计的方法和系统。 训练模块确定训练图像序列和训练图像序列中的对象的姿态表示之间的映射函数。 训练图像序列由一组外观和运动补丁表示。 将一组滤镜应用于外观和运动补片以提取训练图像的特征。 基于提取的特征，训练模块学习将运动和外观补片映射到对象的姿态表示的多维映射函数。 测试模块通过将学习的映射函数应用于测试图像序列来输出快速人体姿态估计。
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5.发明申请OPTICAL CHARACTER RECOGNITION BY ITERATIVE RE-SEGMENTATION OF TEXT IMAGES USING HIGH-LEVEL CUES 审中-公开通过使用高级别的文本图像迭代重新分类来进行光学字符识别公开(公告)号：US20150055866A1
公开(公告)日：2015-02-26
申请号：US13480728
申请日：2012-05-25
IPC分类号： G06K9/34
CPC分类号： G06K9/344 , G06K9/723 , G06K2209/01
摘要： Disclosed techniques include receiving an electronic image containing depictions of characters, segmenting at least some of the depictions of characters using a first segmentation technique to produce a first segmented portion, and performing a first character recognition on the first segmented portion to determine a first sequence of characters. The techniques also include determining, based on the performing the first character recognition, that the first sequence of characters does not match the depictions of characters. The techniques further include segmenting at least some of the depictions of characters using a second segmentation technique, based on the determining, to produce a second segmented portion, and performing a second character recognition on at least a portion of the second segmented portion to produce a second sequence of characters. The techniques also include outputting a third sequence of characters based on at least part of the second sequence of characters.
摘要翻译： 所公开的技术包括接收包含字符描述的电子图像，使用第一分割技术分割至少一些字符描绘以产生第一分段部分，以及在第一分段部分上执行第一字符识别以确定第一序列 人物。 这些技术还包括基于执行第一字符识别确定第一字符序列与字符的描绘不匹配。 所述技术还包括基于确定产生第二分割部分并且在第二分割部分的至少一部分上执行第二字符识别来使用第二分割技术来分割字符的至少一些描绘，以产生 第二个字符序列。 这些技术还包括基于第二个字符序列的至少一部分来输出第三个字符序列。
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公开(公告)号：US08718365B1
公开(公告)日：2014-05-06
申请号：US12608877
申请日：2009-10-29
申请人： Alessandro Bissacco , Hartmut Neven
发明人： Alessandro Bissacco , Hartmut Neven
CPC分类号： G06K9/34 , G06K9/32 , G06K9/3208 , G06K9/3233 , G06K9/342 , G06K9/6857 , G06K2209/01
摘要： A text recognition server is configured to recognize text in a sparse text image. Specifically, given an image, the server specifies a plurality of “patches” (blocks of pixels within the image). The system applies a text detection algorithm to the patches to determine a number of the patches that contain text. This application of the text detection algorithm is used both to estimate the orientation of the image and to determine whether the image is textually sparse or textually dense. If the image is determined to be textually sparse, textual patches are identified and grouped into text regions, each of which is then separately processed by an OCR algorithm, and the recognized text for each region is combined into a result for the image as a whole.
摘要翻译： 文本识别服务器被配置为识别稀疏文本图像中的文本。 具体地，给定图像，服务器指定多个“补丁”（图像内的像素块）。 系统将文本检测算法应用于修补程序，以确定包含文本的多个修补程序。 文本检测算法的这种应用被用于估计图像的取向并确定图像是文本稀疏的还是文本密集的。 如果图像被确定为文本上稀疏的，则文本补丁被识别并分组成文本区域，然后每个文本区域被OCR算法分开处理，并且将每个区域的识别文本合并为整个图像的结果 。
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公开(公告)号：US08345921B1
公开(公告)日：2013-01-01
申请号：US12453432
申请日：2009-05-11
申请人： Andrea Frome , German Cheung , Ahmad Abdulkader , Marco Zennaro , Bo Wu , Alessandro Bissacco , Hartmut Neven , Luc Vincent , Hartwig Adam
发明人： Andrea Frome , German Cheung , Ahmad Abdulkader , Marco Zennaro , Bo Wu , Alessandro Bissacco , Hartmut Neven , Luc Vincent , Hartwig Adam
IPC分类号： G06K9/00
CPC分类号： G06K9/00624 , G06K9/00228 , G06K9/00771 , G06K9/00791 , G06K9/72 , G06K2209/15
摘要： Embodiments of this invention relate to detecting and blurring images. In an embodiment, a system detects objects in a photographic image. The system includes an object detector module configured to detect regions of the photographic image that include objects of a particular type at least based on the content of the photographic image. The system further includes a false positive detector module configured to determine whether each region detected by the object detector module includes an object of the particular type at least based on information about the context in which the photographic image was taken.
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公开(公告)号：US20120008865A1
公开(公告)日：2012-01-12
申请号：US13181081
申请日：2011-07-12
申请人： Bo Wu , Alessandro Bissacco , Raymond W. Smith , Kong man Cheung , Andrea Frome , Shlomo Urbach
发明人： Bo Wu , Alessandro Bissacco , Raymond W. Smith , Kong man Cheung , Andrea Frome , Shlomo Urbach
CPC分类号： G06K9/3258 , G06K9/00 , G06K9/18 , G06K2209/01 , G06Q50/10
摘要： A system and method is provided for automatically recognizing building numbers in street level images. In one aspect, a processor selects a street level image that is likely to be near an address of interest. The processor identifies those portions of the image that are visually similar to street numbers, and then extracts the numeric values of the characters displayed in such portions. If an extracted value corresponds with the building number of the address of interest such as being substantially equal to the address of interest, the extracted value and the image portion are displayed to a human operator. The human operator confirms, by looking at the image portion, whether the image portion appears to be a building number that matches the extracted value. If so, the processor stores a value that associates that building number with the street level image.
摘要翻译： 提供了一种用于自动识别街道图像中的建筑物编号的系统和方法。 在一个方面，处理器选择可能靠近感兴趣的地址的街道级图像。 处理器识别图像中与街道号码视觉相似的那些部分，然后提取在这些部分中显示的字符的数值。 如果提取的值对应于感兴趣的地址的建筑物号码，例如基本上等于感兴趣的地址，则提取的值和图像部分被显示给人类操作者。 人类操作者通过观察图像部分来确认图像部分是否看起来是与提取的值相匹配的建筑物号码。 如果是这样，处理器存储将建筑物号码与街道图像相关联的值。
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9.发明授权Systems and methods for selecting interest point descriptors for object recognition 有权用于选择对象识别的兴趣点描述符的系统和方法公开(公告)号：US08086616B1
公开(公告)日：2011-12-27
申请号：US12404857
申请日：2009-03-16
IPC分类号： G06F7/00
CPC分类号： G06K9/623
摘要： Systems and methods for selecting interest point descriptors for object recognition. In an embodiment, the present invention estimates performance of local descriptors by (1) receiving a local descriptor relating to an object in a first image; (2) identifying one or more nearest neighbor descriptors relating to one or more images different from the first image, the nearest neighbor descriptors comprising nearest neighbors of the local descriptor; (3) calculating a quality score for the local descriptor based on the number of nearest neighbor descriptors that relate to images showing the object; and (4) determining, on the basis of the quality score, if the local descriptor is effective in identifying the object.
摘要翻译： 用于选择对象识别的兴趣点描述符的系统和方法。 在一个实施例中，本发明通过（1）接收与第一图像中的对象有关的局部描述符来估计本地描述符的性能; （2）识别与不同于第一图像的一个或多个图像相关的一个或多个最近邻描述符，最近邻描述符包括本地描述符的最近邻; （3）基于与显示对象的图像相关的最近邻描述符的数量来计算本地描述符的质量得分; 以及（4）基于质量分数来确定本地描述符是否有效地识别对象。
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公开(公告)号：US08787673B2
公开(公告)日：2014-07-22
申请号：US13181081
申请日：2011-07-12
申请人： Bo Wu , Alessandro Bissacco , Raymond W. Smith , Kong man Cheung , Andrea Frome , Shlomo Urbach
发明人： Bo Wu , Alessandro Bissacco , Raymond W. Smith , Kong man Cheung , Andrea Frome , Shlomo Urbach
IPC分类号： G06K9/18
CPC分类号： G06K9/3258 , G06K9/00 , G06K9/18 , G06K2209/01 , G06Q50/10
摘要： A system and method is provided for automatically recognizing building numbers in street level images. In one aspect, a processor selects a street level image that is likely to be near an address of interest. The processor identifies those portions of the image that are visually similar to street numbers, and then extracts the numeric values of the characters displayed in such portions. If an extracted value corresponds with the building number of the address of interest such as being substantially equal to the address of interest, the extracted value and the image portion are displayed to a human operator. The human operator confirms, by looking at the image portion, whether the image portion appears to be a building number that matches the extracted value. If so, the processor stores a value that associates that building number with the street level image.
摘要翻译： 提供了一种用于自动识别街道图像中的建筑物编号的系统和方法。 在一个方面，处理器选择可能靠近感兴趣的地址的街道级图像。 处理器识别图像中与街道号码视觉相似的那些部分，然后提取在这些部分中显示的字符的数值。 如果提取的值对应于感兴趣的地址的建筑物号码，例如基本上等于感兴趣的地址，则提取的值和图像部分被显示给人类操作者。 人类操作者通过观察图像部分来确认图像部分是否看起来是与提取的值相匹配的建筑物号码。 如果是这样，处理器存储将建筑物号码与街道图像相关联的值。
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