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公开(公告)号：US09396621B2
公开(公告)日：2016-07-19
申请号：US13428982
申请日：2012-03-23
CPC分类号： G06K9/00771 , G06K7/10009 , G06K9/00335 , G06K9/6256 , G06K9/6269 , G07G1/0036 , G07G1/0045 , G07G1/009 , H04N7/18 , H04N7/183
摘要： Embodiments of the present invention provide a system, method, and program product to determine whether a product has been successfully purchased by identifying in a video record when a movement of a product adjacent to a scanner occurs, and whether the scanner did not record a purchase transaction at that time; measuring a difference in time between the time of the movement of the product and a time of another movement of a product, and determining by a trained support vector machine a likelihood that the product was successfully purchased. Alternately, the difference in time can be measured between the time of the movement of the product and a time of a transaction record, or between the time of the movement of the product and a boundary time. The support vector machine can use a radial basis function kernel and can generate a decision value and a confidence score.
摘要翻译： 本发明的实施例提供一种系统，方法和程序产品，用于通过在与扫描仪相邻的产品的移动发生时识别产品在视频记录中是否成功购买，以及扫描仪是否没有记录购买 当时交易; 测量产品移动时间与产品的另一次移动时间之间的时间差，以及由经过训练的支持向量机确定产品被成功购买的可能性。 或者，可以在产品移动时间与交易记录时间之间，或在产品移动时间与边界时间之间测量时间差。 支持向量机可以使用径向基函数内核，并可以生成决策值和置信度分数。
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公开(公告)号：US09330315B2
公开(公告)日：2016-05-03
申请号：US13591530
申请日：2012-08-22
CPC分类号： G06K9/00771 , G06T7/11 , G06T7/143 , G06T7/194 , G06T2207/30232
摘要： A computer identifies a proto-object in a digital image using a background subtraction method, the proto-object being associated with a lighting artifact in the surveillance region. The background subtraction method preserves boundary details and interior texture details of proto-objects associated with lighting artifacts. A plurality of characteristics of the proto-object digital data are determined, the characteristics, individually or in combination, distinguish a proto-object related to a lighting artifact from its background. A learning machine, trained with the plurality of characteristics of proto-objects classified as either foreground or not foreground, determines a likelihood that the plurality of characteristics is associated with a foreground object.
摘要翻译： 计算机使用背景减法方法识别数字图像中的原型对象，原型对象与监视区域中的照明伪像相关联。 背景减法方法保留与照明伪像相关联的原始对象的边界细节和内部纹理细节。 确定原始对象数字数据的多个特征，特征单独或组合地将与照明伪影相关的原始物体与其背景区分开。 用分类为前景或非前景的原型对象的多个特征训练的学习机器确定多个特征与前景对象相关联的可能性。
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公开(公告)号：US08682032B2
公开(公告)日：2014-03-25
申请号：US13213262
申请日：2011-08-19
申请人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Jiyan Pan , Sharathchandra U. Pankanti , Hoang Trinh
发明人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Jiyan Pan , Sharathchandra U. Pankanti , Hoang Trinh
IPC分类号： G06K9/62
CPC分类号： G06K9/6292 , G06K9/6885
摘要： Events are classified through string pattern recognition. Text labels are assigned to image primitives in a time-ordered set of training images and to related time-ordered transactions in an associated training transaction log in a combined time-ordered training string of text labels as a function of image types. Transactions are labeled in a training transaction log with a transaction label, a training primitive image of a start of a transaction with a start image text label, a training primitive of an entry of a transaction into the log with an entry image text label, and a training primitive of a conclusion of a transaction with an ending image text label. Positive subset string patterns are discovered representing true events from the combined time-ordered training string of text labels, and negative subset string patterns defined by removing single transaction primitive labels from the positive subset string patterns.
摘要翻译： 事件通过字符串模式识别分类。 将文本标签分配给训练图像的时间有序集合中的图像原语以及相关联的训练事务日志中的相关时间顺序事务，其中文本标签的组合时间有序训练串作为图像类型的函数。 事务在具有事务标签的训练事务日志中被标记，具有开始图像文本标签的事务开始的训练原始图像，具有条目图像文本标签的事务入口的训练原语以及 与结束图像文本标签交易结论的训练原语。 从组合的时间有序的文本标签的训练串中发现表示真实事件的正的子集字符串模式，以及通过从正的子集字符串模式中去除单个事务原始标签而定义的负子集串模式。
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公开(公告)号：US20110280547A1
公开(公告)日：2011-11-17
申请号：US12986233
申请日：2011-01-07
IPC分类号： H04N5/91
CPC分类号： G06K9/00355 , G06T7/20 , G08B13/196
摘要： Video analytics data is audited through review of selective visual essence subsets of visual images from a visual image stream as a function of a temporal relationship of the essence subset images to a triggering alert event. The visual essence subset comprehends an image contemporaneous with the triggering alert event and one or more other images occurring before or after the contemporaneous image. The generated visual essence is presented for review to determine whether the triggering alert event is a true or false alert, or whether additional data from the visual image stream is required to make such a determination. If determined from the presented visual essence that the additional data is required make the true or false determination, then additional data is presented from the visual image stream for review.
摘要翻译： 通过从可视图像流中检查视觉图像的选择性视觉实质子集作为本质子集图像与触发警报事件的时间关系的函数来审查视频分析数据。 视觉本质子集包括与触发警报事件同时发生的图像以及在同期图像之前或之后发生的一个或多个其它图像。 生成的视觉精华被呈现供审查以确定触发警报事件是真实还是假警报，或者是否需要来自视觉图像流的附加数据进行这样的确定。 如果从呈现的视觉实质确定需要附加数据进行真实或错误的确定，则从视觉图像流中呈现附加数据以供审查。
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公开(公告)号：US08478048B2
公开(公告)日：2013-07-02
申请号：US12832379
申请日：2010-07-08
申请人： Lei Ding , Quanfu Fan , Sharathchandra U. Pankanti
发明人： Lei Ding , Quanfu Fan , Sharathchandra U. Pankanti
CPC分类号： G06K9/00335 , G06K9/00771 , G08B13/19613
摘要： In an embodiment, automated analysis of video data for determination of human behavior includes providing a programmable device that segments a video stream into a plurality of discrete individual frame image primitives which are combined into a visual event that may encompass an activity of concern as a function of a hypothesis. The visual event is optimized by setting a binary variable to true or false as a function of one or more constraints. The optimized visual event is processed in view of associated non-video transaction data and the binary variable by associating the optimized visual event with a logged transaction if associable, issuing an alert if the binary variable is true and the optimized visual event is not associable with the logged transaction, and dropping the optimized visual event if the binary variable is false and the optimized visual event is not associable.
摘要翻译： 在一个实施例中，用于确定人类行为的视频数据的自动分析包括提供将视频流分段成多个离散的单独帧图像原语的可编程设备，其被组合成视觉事件，视觉事件可以包含作为功能的关注活动 一个假设。 通过将二进制变量设置为true或false作为一个或多个约束的函数来优化视觉事件。 考虑到相关联的非视频交易数据和二进制变量，通过将优化的可视事件与记录的事务相关联来处理优化的视觉事件，如果可关联，则如果二进制变量为真，并且优化的视觉事件不能与 记录的事务，并且如果二进制变量为false并且优化的可视事件不可关联，则丢弃优化的可视事件。
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公开(公告)号：US20130044942A1
公开(公告)日：2013-02-21
申请号：US13213262
申请日：2011-08-19
申请人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Jiyan Pan , Sharathchandra U. Pankanti , Hoang Trinh
发明人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Jiyan Pan , Sharathchandra U. Pankanti , Hoang Trinh
IPC分类号： G06K9/62
CPC分类号： G06K9/6292 , G06K9/6885
摘要： Events are classified through string pattern recognition. Text labels are assigned to image primitives in a time-ordered set of training images and to related time-ordered transactions in an associated training transaction log in a combined time-ordered training string of text labels as a function of image types. Transactions are labeled in a training transaction log with a transaction label, a training primitive image of a start of a transaction with a start image text label, a training primitive of an entry of a transaction into the log with an entry image text label, and a training primitive of a conclusion of a transaction with an ending image text label. Positive subset string patterns are discovered representing true events from the combined time-ordered training string of text labels, and negative subset string patterns defined by removing single transaction primitive labels from the positive subset string patterns.
摘要翻译： 事件通过字符串模式识别分类。 将文本标签分配给训练图像的时间有序集合中的图像原语以及相关联的训练事务日志中的相关时间顺序事务，其中文本标签的组合时间有序训练串作为图像类型的函数。 事务在具有事务标签的训练事务日志中被标记，具有开始图像文本标签的事务开始的训练原始图像，具有条目图像文本标签的事务入口的训练原语以及 与结束图像文本标签交易结论的训练原语。 从组合的时间有序的文本标签的训练串中发现表示真实事件的正的子集字符串模式，以及通过从正的子集字符串模式中去除单个事务原始标签而定义的负子集串模式。
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公开(公告)号：US20120008819A1
公开(公告)日：2012-01-12
申请号：US12832379
申请日：2010-07-08
申请人： Lei Ding , Quanfu Fan , Sharathchandra U. Pankanti
发明人： Lei Ding , Quanfu Fan , Sharathchandra U. Pankanti
IPC分类号： G06K9/00
CPC分类号： G06K9/00335 , G06K9/00771 , G08B13/19613
摘要： In an embodiment, automated analysis of video data for determination of human behavior includes providing a programmable device that segments a video stream into a plurality of discrete individual frame image primitives which are combined into a visual event that may encompass an activity of concern as a function of a hypothesis. The visual event is optimized by setting a binary variable to true or false as a function of one or more constraints. The optimized visual event is processed in view of associated non-video transaction data and the binary variable by associating the optimized visual event with a logged transaction if associable, issuing an alert if the binary variable is true and the optimized visual event is not associable with the logged transaction, and dropping the optimized visual event if the binary variable is false and the optimized visual event is not associable.
摘要翻译： 在一个实施例中，用于确定人类行为的视频数据的自动分析包括提供将视频流分段成多个离散的单独帧图像原语的可编程设备，其被组合成视觉事件，视觉事件可以包含作为功能的关注活动 一个假设。 通过将二进制变量设置为true或false作为一个或多个约束的函数来优化视觉事件。 考虑到相关联的非视频交易数据和二进制变量，通过将优化的可视事件与记录的事务相关联来处理优化的视觉事件，如果可关联，则如果二进制变量为真，并且优化的视觉事件不能与 记录的事务，并且如果二进制变量为false并且优化的可视事件不可关联，则丢弃优化的可视事件。
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38.发明申请公开(公告)号：US20130250115A1
公开(公告)日：2013-09-26
申请号：US13428982
申请日：2012-03-23
CPC分类号： G06K9/00771 , G06K7/10009 , G06K9/00335 , G06K9/6256 , G06K9/6269 , G07G1/0036 , G07G1/0045 , G07G1/009 , H04N7/18 , H04N7/183
摘要： Embodiments of the present invention provide a system, method, and program product to determine whether a product has been successfully purchased by identifying in a video record when a movement of a product adjacent to a scanner occurs, and whether the scanner did not record a purchase transaction at that time; measuring a difference in time between the time of the movement of the product and a time of another movement of a product, and determining by a trained support vector machine a likelihood that the product was successfully purchased. Alternately, the difference in time can be measured between the time of the movement of the product and a time of a transaction record, or between the time of the movement of the product and a boundary time. The support vector machine can use a radial basis function kernel and can generate a decision value and a confidence score.
摘要翻译： 本发明的实施例提供一种系统，方法和程序产品，用于通过在与扫描仪相邻的产品的移动发生时识别产品在视频记录中是否成功购买，以及扫描仪是否没有记录购买 当时交易; 测量产品移动时间与产品的另一次移动时间之间的时间差，以及由经过训练的支持向量机确定产品被成功购买的可能性。 或者，可以在产品移动时间与交易记录时间之间，或在产品移动时间与边界时间之间测量时间差。 支持向量机可以使用径向基函数内核，并可以生成决策值和置信度分数。
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公开(公告)号：US20130050517A1
公开(公告)日：2013-02-28
申请号：US13218845
申请日：2011-08-26
CPC分类号： G06K9/00 , G06K9/00771 , H04N5/232 , H04N5/23222
摘要： Visual content in images captured from a scene by a camera in each of a plurality of different pose settings are analyzed to determine predicted occurrences of a transaction associated with the visual content in each pose, which are compared with actual transaction occurrence data to generate performance values for each pose as a function difference between the predicted and actual transactions. Optimized poses are chosen having the best performance value, wherein a camera controller may place the camera in the optimum pose for use in monitoring the scene and generating the primitives of interest associated with the transactions.
摘要翻译： 分析由多个不同姿势设置中的每一个中的摄像机从场景捕获的图像中的视觉内容，以确定与每个姿态中的视觉内容相关联的事务的预测出现，其与实际交易发生数据进行比较以生成性能值 对于每个姿势作为预测和实际交易之间的功能差异。 选择具有最佳性能值的优化姿态，其中相机控制器可将相机放置在用于监视场景的最佳姿态并产生与交易相关联的感兴趣的原始图案。
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公开(公告)号：US20120293661A1
公开(公告)日：2012-11-22
申请号：US13559996
申请日：2012-07-27
申请人： Russell Patrick Bobbitt , Quanfu Fan , Sachiko Miyazawa , Sharathchandra Umapathirao Pankanti , Yun Zhai
发明人： Russell Patrick Bobbitt , Quanfu Fan , Sachiko Miyazawa , Sharathchandra Umapathirao Pankanti , Yun Zhai
IPC分类号： H04N7/18
CPC分类号： G06K9/00771 , G06K9/00993 , G06Q20/202 , H04N7/181 , H04N7/188
摘要： An approach to reduce the processing power required to monitor check-out stations. A subset of check-out stations may be monitored at any given time, instead of monitoring all check-out stations at all times. The subset of check-out stations is determined dynamically according to, but not limited to, cashier records, input parameters from the user, current lane activity, past lane activity, time of day, etc. Statistical models (e.g., effective population sampling and/or population hypothesis tests) are developed along these lines that guide the lane selection process, whereby increases in the false-negative rate due to failure to monitor particular lanes when events of interest occur are controlled. By monitoring fewer check-out stations, while maintaining target performance accuracy, the amount of data that end users must deal with is significantly reduced.
摘要翻译： 一种降低监控检查站所需的处理能力的方法。 可以在任何给定的时间监视检验站的子集，而不是始终监视所有的检出站。 根据但不限于出纳员记录，来自用户的输入参数，当前车道活动，过去车道活动，时间等，动态地确定检出站的子集。统计模型（例如，有效人口抽样和 /或群体假设检验）沿着这些线路开发，指导车道选择过程，由此控制在感兴趣事件发生时由于不监视特定车道而导致的假阴性率的增加。 通过监控较少的检出站，同时保持目标性能的准确性，最终用户必须处理的数据量显着降低。
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