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1. 发明授权

US08682032B2 Event detection through pattern discovery 有权
标题翻译：通过模式发现进行事件检测
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。

2. 发明申请

US20130044942A1 EVENT DETECTION THROUGH PATTERN DISCOVERY 有权
标题翻译：通过图案发现的事件检测
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。

3. 发明申请

US20130050517A1 VISUAL CONTENT-AWARE AUTOMATIC CAMERA ADJUSTMENT 失效
标题翻译：视觉内容自动相机调整
公开(公告)号：US20130050517A1
公开(公告)日：2013-02-28
申请号：US13218845
申请日：2011-08-26
申请人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
发明人： Quanfu Fan , Prasad Gabbur , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
IPC分类号： H04N5/228 , G06K9/00
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。

4. 发明授权

US08582803B2 Event determination by alignment of visual and transaction data 有权
标题翻译：事件确定通过对齐视觉和交易数据
公开(公告)号：US08582803B2
公开(公告)日：2013-11-12
申请号：US12905272
申请日：2010-10-15
申请人： Lei Ding , Quanfu Fan , Prasad Gabbur , Arun Hampapur , Sachiko Miyazawa , Sharathchandra U. Pankanti
发明人： Lei Ding , Quanfu Fan , Prasad Gabbur , Arun Hampapur , Sachiko Miyazawa , Sharathchandra U. Pankanti
IPC分类号： G06K9/00
CPC分类号： G06K9/6215 , G06K9/00335 , G06K9/00771
摘要： Determination of human behavior from an alignment of data streams includes acquiring visual image primitives from a video input comprising visual information relevant to a human activity. The primitives are temporally aligned to an optimally hypothesized sequence of primitives transformed from a sequence of transactions as a function of a distance metric between the observed primitive sequence and the transformed primitive sequence. More particularly, transforming includes comparing the distance metric costs and choosing and performing the lowest cost of temporally matching the observed primitives to one or more transactions, deleting a primitive, or associating a primitive with a pseudo transaction marker. Accordingly, alerts are issued based on analysis of the transformation of primitives.
摘要翻译：从数据流的对齐确定人类行为包括从包括与人类活动相关的视觉信息的视频输入中获取视觉图像原语。原语在时间上与从事件序列变换的最优假设序列的原语对齐，作为观察到的原始序列与经变换的原始序列之间的距离度量的函数。更具体地，变换包括比较距离度量成本并选择和执行将观察到的原语暂时匹配到一个或多个事务，删除原语或将原语与伪交易标记相关联的最低成本。因此，基于对原语的转换的分析发出警报。

5. 发明申请

US20120093370A1 EVENT DETERMINATION BY ALIGNMENT OF VISUAL AND TRANSACTION DATA 有权
标题翻译：通过视觉和交易数据的对齐确定事件
公开(公告)号：US20120093370A1
公开(公告)日：2012-04-19
申请号：US12905272
申请日：2010-10-15
申请人： Lei Ding , Quanfu Fan , Prasad Gabbur , Arun Hampapur , Sachiko Miyazawa , Sharathchandra U. Pankanti
发明人： Lei Ding , Quanfu Fan , Prasad Gabbur , Arun Hampapur , Sachiko Miyazawa , Sharathchandra U. Pankanti
IPC分类号： G06K9/00
CPC分类号： G06K9/6215 , G06K9/00335 , G06K9/00771
摘要： Determination of human behavior from an alignment of data streams includes acquiring visual image primitives from a video input comprising visual information relevant to a human activity. The primitives are temporally aligned to an optimally hypothesized sequence of primitives transformed from a sequence of transactions as a function of a distance metric between the observed primitive sequence and the transformed primitive sequence. More particularly, transforming includes comparing the distance metric costs and choosing and performing the lowest cost of temporally matching the observed primitives to one or more transactions, deleting a primitive, or associating a primitive with a pseudo transaction marker. Accordingly, alerts are issued based on analysis of the transformation of primitives.
摘要翻译：从数据流的对齐确定人类行为包括从包括与人类活动相关的视觉信息的视频输入中获取视觉图像原语。原语在时间上与从事件序列变换的最优假设序列的原语对齐，作为观察到的原始序列与经变换的原始序列之间的距离度量的函数。更具体地，变换包括比较距离度量成本并选择和执行将观察到的原语暂时匹配到一个或多个事务，删除原语或将原语与伪交易标记相关联的最低成本。因此，基于对原语的转换的分析发出警报。

6. 发明授权

US09396621B2 Systems and methods for false alarm reduction during event detection 有权
标题翻译：事件检测过程中虚报警减少的系统和方法
公开(公告)号：US09396621B2
公开(公告)日：2016-07-19
申请号：US13428982
申请日：2012-03-23
申请人： Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
发明人： Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
IPC分类号： G06K9/00 , H04N9/47 , H04N7/18 , G07G1/00 , G06K9/62
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。

7. 发明申请

US20130250115A1 SYSTEMS AND METHODS FOR FALSE ALARM REDUCTION DURING EVENT DETECTION 有权
标题翻译：在事件检测期间进行伪报警减少的系统和方法
公开(公告)号：US20130250115A1
公开(公告)日：2013-09-26
申请号：US13428982
申请日：2012-03-23
申请人： Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
发明人： Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Hoang Trinh
IPC分类号： G06K9/62 , H04N7/18
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。

8. 发明申请

US20120008836A1 SEQUENTIAL EVENT DETECTION FROM VIDEO 有权
标题翻译：视频中的顺序事件检测
公开(公告)号：US20120008836A1
公开(公告)日：2012-01-12
申请号：US12834104
申请日：2010-07-12
申请人： Russell P. Bobbitt , Lei Ding , Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Yun Zhai
发明人： Russell P. Bobbitt , Lei Ding , Quanfu Fan , Sachiko Miyazawa , Sharathchandra U. Pankanti , Yun Zhai
IPC分类号： G06K9/00 , G06T11/20
CPC分类号： G06K9/00335 , G06K9/00771 , G06K9/6224
摘要： Human behavior is determined by sequential event detection by constructing a temporal-event graph with vertices representing adjacent first and second primitive images of a plurality of individual primitive images parsed from a video stream, and also of first and second idle states associated with the respective first and second primitive images. Constructing the graph is a function of an edge set between the adjacent first and second primitive images, and an edge weight set as a function of a discrepancy between computed visual features within regions of interest common to the adjacent first and second primitive images. A human activity event is determined as a function of a shortest distance path of the temporal-event graph vertices.
摘要翻译：通过构建具有表示从视频流解析的多个单独原始图像的相邻第一和第二原始图像的顶点的时间事件图以及与各自的第一和第二空闲状态相关联的第一和第二空闲状态，通过顺序事件检测来确定人的行为和第二原始图像。构造图是在相邻的第一和第二原始图像之间设置的边缘的函数，以及作为相邻第一和第二原始图像共同的感兴趣区域内的计算的视觉特征之间的差异的函数的边缘权重集合。人类活动事件被确定为时间 - 事件图形顶点的最短距离路径的函数。

9. 发明授权

US08744123B2 Modeling of temporarily static objects in surveillance video data 有权
标题翻译：监控视频数据中临时静态对象的建模
公开(公告)号：US08744123B2
公开(公告)日：2014-06-03
申请号：US13220213
申请日：2011-08-29
申请人： Russell P. Bobbitt , Quanfu Fan , Zuoxuan Lu , Jiyan Pan , Sharathchandra U. Pankanti
发明人： Russell P. Bobbitt , Quanfu Fan , Zuoxuan Lu , Jiyan Pan , Sharathchandra U. Pankanti
IPC分类号： G06K9/00
CPC分类号： G06K9/00771
摘要： A foreground object blob having a bounding box detected in frame image data is classified by a finite state machine as a background, moving foreground, or temporally static object, namely as the temporally static object when the detected bounding box is distinguished from a background model of a scene image of the video data input and remains static in the scene image for a threshold period. The bounding box is tracked through matching masks in subsequent frame data of the video data input, and the object sub-classified within a visible sub-state, an occluded sub-state, or another sub-state that is not visible and not occluded as a function of a static value ratio. The ratio is a number of pixels determined to be static by tracking in a foreground region of the background model corresponding to the tracked object bounding box over a total number of pixels of the foreground region.
摘要翻译：在帧图像数据中检测到的具有边界框的前景对象斑点被分类为有限状态机作为背景，移动前景或时间静态对象，即当检测到的边界框与背景模型输入视频数据的场景图像，并在场景图像中保持静止阈值周期。通过视频数据输入的后续帧数据中的匹配掩码来跟踪边界框，并且将子分类在可见子状态，闭塞子状态或不可见并且不被遮挡的另一子状态中的对象作为静态值比的函数。所述比例是通过在前景区域的总数目的像素对应于跟踪对象边界框的背景模型的前景区域中进行跟踪而确定为静态的像素的数量。

10. 发明申请

US20130051613A1 MODELING OF TEMPORARILY STATIC OBJECTS IN SURVEILLANCE VIDEO DATA 有权
标题翻译：在监视视频数据中建立临时静态对象
公开(公告)号：US20130051613A1
公开(公告)日：2013-02-28
申请号：US13220213
申请日：2011-08-29
申请人： Russell P. Bobbitt , Quanfu Fan , Zuoxuan Lu , Jiyan Pan , Sharathchandra U. Pankanti
发明人： Russell P. Bobbitt , Quanfu Fan , Zuoxuan Lu , Jiyan Pan , Sharathchandra U. Pankanti
IPC分类号： G06K9/00
CPC分类号： G06K9/00771
摘要： A foreground object blob having a bounding box detected in frame image data is classified by a finite state machine as a background, moving foreground, or temporally static object, namely as the temporally static object when the detected bounding box is distinguished from a background model of a scene image of the video data input and remains static in the scene image for a threshold period. The bounding box is tracked through matching masks in subsequent frame data of the video data input, and the object sub-classified within a visible sub-state, an occluded sub-state, or another sub-state that is not visible and not occluded as a function of a static value ratio. The ratio is a number of pixels determined to be static by tracking in a foreground region of the background model corresponding to the tracked object bounding box over a total number of pixels of the foreground region.
摘要翻译：在帧图像数据中检测到的具有边界框的前景对象斑点被分类为有限状态机作为背景，移动前景或时间静态对象，即当检测到的边界框与背景模型输入视频数据的场景图像，并在场景图像中保持静止阈值周期。通过视频数据输入的后续帧数据中的匹配掩码来跟踪边界框，并且将子分类在可见子状态，闭塞子状态或不可见并且不被遮挡的另一子状态中的对象作为静态值比的函数。所述比例是通过在前景区域的总数目的像素对应于跟踪对象边界框的背景模型的前景区域中进行跟踪而确定为静态的像素的数量。

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