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公开(公告)号：US20140055609A1
公开(公告)日：2014-02-27
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：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：US08610766B2
公开(公告)日：2013-12-17
申请号：US12890007
申请日：2010-09-24
CPC分类号： G06K9/6284 , G06K9/00335 , G06K9/00771 , G08B13/19613
摘要： Human behavior alerts are determined from a video stream through application of video analytics that parse a video stream into a plurality of segments, wherein each of the segments are either temporally related to at least one of a plurality of temporally distinct transactions in an event data log; or they are each associated with a pseudo transaction marker if not temporally related to at least one of the temporally distinct transactions and an image analysis indicates a temporal correlation with at least one of the distinct transactions is expected. Visual image features are extracted from the segments and one-SVM classification is performed on the extracted features to categorize segments into inliers or outliers relative to a threshold boundary. Event of concern alerts are issued with respect to the inlier segments associated with the associated pseudo transaction marker.
摘要翻译： 通过应用将视频流解析成多个段的视频分析从视频流确定人的行为警报，其中每个段在时间上与事件数据日志中的多个时间上不同的事务中的至少一个相关 ; 或者如果与时间上不同的交易中的至少一个时间上不相关，并且图像分析指示与至少一个不同交易的时间相关性，则它们都与伪交易标记相关联。 从段中提取视觉图像特征，并且对所提取的特征执行单SVM分类，以将段分类为相对于阈值边界的内联或异常值。 关于与相关联的伪交易标记相关联的不规则段发出关注警报的事件。
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公开(公告)号：US20120075450A1
公开(公告)日：2012-03-29
申请号：US12890007
申请日：2010-09-24
CPC分类号： G06K9/6284 , G06K9/00335 , G06K9/00771 , G08B13/19613
摘要： Human behavior alerts are determined from a video stream through application of video analytics that parse a video stream into a plurality of segments, wherein each of the segments are either temporally related to at least one of a plurality of temporally distinct transactions in an event data log; or they are each associated with a pseudo transaction marker if not temporally related to at least one of the temporally distinct transactions and an image analysis indicates a temporal correlation with at least one of the distinct transactions is expected. Visual image features are extracted from the segments and one-SVM classification is performed on the extracted features to categorize segments into inliers or outliers relative to a threshold boundary. Event of concern alerts are issued with respect to the inlier segments associated with the associated pseudo transaction marker.
摘要翻译： 通过应用将视频流解析成多个段的视频分析从视频流确定人的行为警报，其中每个段在时间上与事件数据日志中的多个时间上不同的事务中的至少一个相关 ; 或者如果与时间上不同的交易中的至少一个时间上不相关，并且图像分析指示与至少一个不同交易的时间相关性，则它们都与伪交易标记相关联。 从段中提取视觉图像特征，并且对所提取的特征执行单SVM分类，以将段分类为相对于阈值边界的内联或异常值。 关于与相关联的伪交易标记相关联的不规则段发出关注警报的事件。
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15.发明申请SYSTEM AND METHOD FOR AUTOMATICALLY DISTINGUISHING BETWEEN CUSTOMERS AND IN-STORE EMPLOYEES 失效客户和内部员工之间自动辨别的系统和方法公开(公告)号：US20100114802A1
公开(公告)日：2010-05-06
申请号：US12263928
申请日：2008-11-03
CPC分类号： G06N99/005 , G06Q30/06
摘要： An approach that automatically distinguishes between in-store customers and in-store employees is provided. In one embodiment, there is a learning tool configured to construct a model for an in-store employee; and a classifying tool, further comprising matching tool configured to: match attributes between a particular person and the constructed models for an in-store employee, the classifying tool configured to: classify persons into categories of employees and customers based on amount of matching attributes between a particular person and the model for an in-store employee.
摘要翻译： 提供了一种自动区分店内客户和店内员工的方法。 在一个实施例中，存在用于构建店内员工的模型的学习工具; 以及分类工具，还包括匹配工具，其被配置为：匹配特定人员和所述店内员工的所构建的模型之间的属性，所述分类工具被配置为：基于所述员工和所述客户的类别， 一个特定的人和一个店内员工的模型。
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公开(公告)号：US20100114617A1
公开(公告)日：2010-05-06
申请号：US12261256
申请日：2008-10-30
CPC分类号： G08B13/19671 , G06Q20/202 , G06Q20/401 , G06Q30/06 , G06Q40/12
摘要： An approach that detects potentially fraudulent transactions is provided. In one embodiment, there is a fraud detection tool including, an identification component configured to identify a first person present within a zone of interest at a point of sale (POS) device using a set of sensor devices; a transaction component configured to determine whether the POS device has performed a first transaction and a second transaction while the first person is present within the zone of interest at the POS device; an analysis component configured to: analyze a transaction type of the first transaction and the second transaction; and detect whether the second transaction is potentially fraudulent based on a determination of whether the POS device has performed a first transaction and a second transaction while the first person is within the zone of interest at the POS device, and an analysis of the transaction type of the second transaction.
摘要翻译： 提供了一种检测潜在欺诈交易的方法。 在一个实施例中，存在欺诈检测工具，其包括识别组件，其被配置为使用一组传感器设备来识别在销售点（POS）设备处存在于感兴趣区域内的第一人物; 交易组件，被配置为当所述第一人在所述POS设备的所述感兴趣区域内存在时，确定所述POS设备是否已经执行了第一交易和第二交易; 分析组件，其被配置为：分析所述第一事务和所述第二事务的事务类型; 并且当所述第一人在所述POS设备的所述感兴趣区域内时，基于所述POS设备是否已经执行了第一交易和所述第二交易的确定来检测所述第二交易是否具有潜在的欺诈性，以及所述交易类型的分析 第二笔交易。
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公开(公告)号：US20100111404A1
公开(公告)日：2010-05-06
申请号：US12261304
申请日：2008-10-30
申请人： Russell P. Bobbitt , Quanfu Fan , Arun Hampapur , Frederik C. M. Kjeldsen , Sharathchandra U. Pankanti , Akira Yanagawa , Yun Zhai
发明人： Russell P. Bobbitt , Quanfu Fan , Arun Hampapur , Frederik C. M. Kjeldsen , Sharathchandra U. Pankanti , Akira Yanagawa , Yun Zhai
IPC分类号： G06K9/66
CPC分类号： G06K9/00771
摘要： An approach that dynamically learns a set of attributes of an operator of a point of sale (POS) is provided. In one embodiment, there is an attribute tool, including an extraction component configured to receive sensor data of a set of moving objects, and extract a set of attributes from each of the set of moving objects captured within the scan area at the POS; an identification component configured to update an appearance model with the set of attributes from each of the set of moving objects; and an analysis component configured to analyze the appearance model to identify at least one of the set of moving objects as an operator of the POS.
摘要翻译： 提供了动态学习销售点（POS）的运营商的一组属性的方法。 在一个实施例中，存在一种属性工具，包括被配置为接收一组移动对象的传感器数据的提取部件，并且从POS中的扫描区域内捕获的移动对象集合中的每一个提取一组属性; 识别组件，被配置为使用来自所述一组移动对象的所述一组属性来更新外观模型; 以及分析部件，被配置为分析所述外观模型以将所述一组移动对象中的至少一个识别为所述POS的操作者。
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18.发明授权System and method for automatically distinguishing between customers and in-store employees 失效用于自动区分客户和店内员工的系统和方法公开(公告)号：US08694443B2
公开(公告)日：2014-04-08
申请号：US12263928
申请日：2008-11-03
IPC分类号： G06F15/18
CPC分类号： G06N99/005 , G06Q30/06
摘要： An approach that automatically distinguishes between in-store customers and in-store employees is provided. In one embodiment, there is a learning tool configured to construct a model for an in-store employee; a matching tool configured to match attributes between a particular person and the constructed models for an in-store employee; and a classifying tool configured to classify persons into categories of employees and customers based on amount of matching attributes between a particular person and the model for an in-store employee.
摘要翻译： 提供了一种自动区分店内客户和店内员工的方法。 在一个实施例中，存在用于构建店内员工的模型的学习工具; 匹配工具，被配置为匹配特定人员和店内员工的构建模型之间的属性; 以及分类工具，其被配置为基于针对店内员工的特定人与模型之间的匹配属性的数量来将人员分类为雇员和顾客的类别。
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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：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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