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1. 发明授权

US07667596B2 Method and system for scoring surveillance system footage 有权
标题翻译：监视系统镜头评分方法和系统
公开(公告)号：US07667596B2
公开(公告)日：2010-02-23
申请号：US11676127
申请日：2007-02-16
申请人： Hasan Timucin Ozdemir , Sameer Kibey , Lipin Liu , Kuo Chu Lee , Supraja Mosali , Namsoo Joo , Hongbing Li , Juan Yu
发明人： Hasan Timucin Ozdemir , Sameer Kibey , Lipin Liu , Kuo Chu Lee , Supraja Mosali , Namsoo Joo , Hongbing Li , Juan Yu
IPC分类号： G08B13/00
CPC分类号： G08B31/00 , G08B13/196 , G08B21/0423
摘要： A surveillance system generally includes a data capture module that collects sensor data. A scoring engine module receives the sensor data and computes at least one of an abnormality score and a normalcy score based on the sensor data, at least one dynamically loaded learned data model, and a learned scoring method. A decision making module receives the at least one of the abnormality score and the normalcy score and generates an alert message based on the at least one of the abnormality score and the normalcy score and a learned decision making method to produce progressive behavior and threat detection.
摘要翻译：监视系统通常包括收集传感器数据的数据捕获模块。评分引擎模块接收传感器数据，并且基于传感器数据，至少一个动态加载的学习数据模型和学习评分方法来计算异常分数和正常分数中的至少一个。决策模块接收异常分数和正常分数中的至少一个，并且基于异常得分和正常分数中的至少一个产生警报消息，以及学习决策方法来产生渐进行为和威胁检测。

2. 发明授权

US07237260B2 Method for dynamic selection for secure and firewall friendly communication protocols between multiple distributed modules 有权
标题翻译：用于动态选择多个分布式模块之间的安全和防火墙友好通信协议的方法
公开(公告)号：US07237260B2
公开(公告)日：2007-06-26
申请号：US10614909
申请日：2003-07-08
申请人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee , Shiwen Chen , Eimei Nanma
发明人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee , Shiwen Chen , Eimei Nanma
IPC分类号： H04L29/00 , H04L29/06
CPC分类号： H04L63/0272 , H04L63/0823 , H04L63/166
摘要： Distributed modules in a network dynamically select communication protocols to communicate in a secure or firewall-protected network. Applications register with a lookup service. The lookup service maintains a lookup table including registration information for multiple applications. Registration information may include, but is not limited to, IP address, firewall restrictions, tunnel protocol, port information, and proxy queue capabilities. An application seeking to communicate acquires the registration information for a desired recipient from the lookup table. The application uses the registration information to select communication protocols necessary to communicate with the recipient.
摘要翻译：网络中的分布式模块动态选择通信协议，以在安全或防火墙保护的网络中进行通信。应用程序注册一个查找服务。查找服务维护包括多个应用的注册信息的查找表。注册信息可以包括但不限于IP地址，防火墙限制，隧道协议，端口信息和代理队列功能。寻求通信的应用从查找表获取期望的接收者的注册信息。应用程序使用注册信息来选择与接收者通信所需的通信协议。

3. 发明授权

US07962435B2 System architecture and process for seamless adaptation to context aware behavior models 有权
标题翻译：系统架构和过程，用于无缝适应上下文感知行为模型
公开(公告)号：US07962435B2
公开(公告)日：2011-06-14
申请号：US12034164
申请日：2008-02-20
申请人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee
发明人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee
IPC分类号： G06F17/00 , G06N5/02 , G08B13/00
CPC分类号： G06K9/00771 , A61B5/1128 , A61B5/16 , A61B5/7267 , G06K9/00785
摘要： A surveillance system implements an architecture and process to support real-time abnormal behavior assessment operations in a distributed scalable sensor network. An automated behavior model builder generates behavior models from sensor data. A plurality of abnormal behavior scoring engines operating concurrently to generate abnormal behavior assessment models by scoring the behavior models. An execution performance manager performs fast switching of behavior models for the abnormal behavior scoring engines. The execution performance manager performs detection of abnormal behavior score distribution characteristic deviation by comparing a current abnormal behavior assessment model to a pre-recorded abnormal behavior assessment model. The execution performance manager selects a pre-recorded behavior model for the abnormal behavior scoring engines when the deviation exceeds a predetermined threshold.
摘要翻译：监控系统实现一种架构和过程，以支持分布式可扩展传感器网络中的实时异常行为评估操作。自动行为模型构建器从传感器数据生成行为模型。多个异常行为评分引擎同时运行，通过评分行为模型来产生异常行为评估模型。执行性能管理员可以快速切换异常行为评分引擎的行为模型。执行绩效管理者通过将当前的异常行为评估模型与预先记录的异常行为评估模型进行比较来执行异常行为评分分布特征偏差的检测。当偏差超过预定阈值时，执行性能管理器为异常行为评分引擎选择预先记录的行为模型。

4. 发明申请

US20100208063A1 SYSTEM AND METHODS FOR IMPROVING ACCURACY AND ROBUSTNESS OF ABNORMAL BEHAVIOR DETECTION 审中-公开
标题翻译：用于提高异常行为检测精度和鲁棒性的系统和方法
公开(公告)号：US20100208063A1
公开(公告)日：2010-08-19
申请号：US12496681
申请日：2009-07-02
申请人： Kuo Chu Lee , Hasan Timucin Ozdemir , Juan Yu , Xiangjun Shi
发明人： Kuo Chu Lee , Hasan Timucin Ozdemir , Juan Yu , Xiangjun Shi
IPC分类号： G08B21/00 , H04N5/00
CPC分类号： G06T7/20 , G06K9/00771 , G08B13/19608 , G08B13/19613 , G08B13/19641 , H04N7/181
摘要： A surveillance system improves accuracy and robustness of abnormal behavior detection of a monitored object traversing a space includes a metadata processing module, a model building module, and a behavior assessment module. The metadata processing module generates trajectory information for a monitor object and determines attributes of the monitored object. The model building module at least one of generates and updates normal motion models based on at least one of the trajectory information, the attributes, and an abnormal behavior score. The behavior assessment module generates the abnormal behavior score based on one of a plurality of methods. A first one of the plurality of methods defines wrong direction behavior. A second one of the plurality of methods defines wandering/loitering behavior. A third one of the plurality of methods defines speeding behavior.
摘要翻译：监视系统提高了穿过空间的被监视对象的异常行为检测的精度和鲁棒性，包括元数据处理模块，模型构建模块和行为评估模块。元数据处理模块生成监视对象的轨迹信息，并确定被监视对象的属性。模型构建模块至少基于轨迹信息，属性和异常行为得分中的至少一个来生成和更新正常运动模型。行为评估模块基于多种方法之一产生异常行为得分。多种方法中的第一种方法定义了错误的方向行为。多种方法中的第二种方法定义了流浪/游荡行为。多种方法中的第三种方法定义了超速行为。

5. 发明授权

US07567956B2 Distributed meta data management middleware 有权
标题翻译：分布式元数据管理中间件
公开(公告)号：US07567956B2
公开(公告)日：2009-07-28
申请号：US11354774
申请日：2006-02-15
申请人： Juan Yu , Hasan Timucin Ozdemir , Lipin Liu , Kuo Chu Lee
发明人： Juan Yu , Hasan Timucin Ozdemir , Lipin Liu , Kuo Chu Lee
IPC分类号： G06F17/30
CPC分类号： G06F17/30566 , Y10S707/99933 , Y10S707/99945
摘要： A meta data management system for use with a surveillance system includes a user interface that allows users to define rules to manage meta data from distributed devices. An application programming interface provides an application access to system data and control information. A mechanism allows the application to transparently and seamlessly integrate with different types of databases by transparently allocating and searching the data that are physically distributed at different devices.
摘要翻译：用于监视系统的元数据管理系统包括允许用户定义用于管理来自分布式设备的元数据的规则的用户界面。应用编程接口提供对系统数据和控制信息的应用访问。一种机制允许应用程序通过透明地分配和搜索在不同设备上物理分布的数据来透明地和无缝地与不同类型的数据库集成。

6. 发明申请

US20080198159A1 METHOD AND APPARATUS FOR EFFICIENT AND FLEXIBLE SURVEILLANCE VISUALIZATION WITH CONTEXT SENSITIVE PRIVACY PRESERVING AND POWER LENS DATA MINING 审中-公开
标题翻译：有效和灵活监控的方法和设备可视化与上下文敏感隐私保护和功率透镜数据采矿
公开(公告)号：US20080198159A1
公开(公告)日：2008-08-21
申请号：US11675942
申请日：2007-02-16
申请人： Lipin LIU , Kuo Chu Lee , Juan Yu , Hasan Timucin Ozdemir , Norihiro Kondo
发明人： Lipin LIU , Kuo Chu Lee , Juan Yu , Hasan Timucin Ozdemir , Norihiro Kondo
IPC分类号： G06T17/10
CPC分类号： G08B13/19671 , G08B13/19641 , G08B13/1968 , G08B13/19686
摘要： The surveillance visualization system extracts information from plural cameras to generate a graphical representation of a scene, with stationary entities such as buildings and trees represented by graphical model and with moving entities such as cars and people represented by separate dynamic objects that can be coded to selectively reveal or block the identity of the entity for privacy protection. A power lens tool allows users to specify and retrieve results of data mining operations applied to a metadata store linked with objects in the scene. A distributed model is presented where a grid or matrix is used to define data mining conditions and to present the results in a variety of different formats. The system supports use by multiple persons who can share metadata and data mining queries with one another.
摘要翻译：监视可视化系统从多个摄像机中提取信息以生成场景的图形表示，其中包括由图形模型表示的诸如建筑物和树木的静止实体以及由分离的动态对象表示的移动实体（例如汽车和人），其可被编码为选择性地揭露或阻止实体的身份进行隐私保护。功率透镜工具允许用户指定和检索应用于与场景中的对象相关联的元数据存储的数据挖掘操作的结果。提出了一种分布式模型，其中使用网格或矩阵来定义数据挖掘条件并以各种不同的格式呈现结果。该系统支持可以彼此共享元数据和数据挖掘查询的多个人使用。

7. 发明授权

US08253564B2 Predicting a future location of a moving object observed by a surveillance device 有权
标题翻译：预测监视装置观察到的移动物体的未来位置
公开(公告)号：US08253564B2
公开(公告)日：2012-08-28
申请号：US12496724
申请日：2009-07-02
申请人： Kuo Chu Lee , Hasan Timucin Ozdemir , Juan Yu
发明人： Kuo Chu Lee , Hasan Timucin Ozdemir , Juan Yu
IPC分类号： G08B21/00
CPC分类号： G06K9/00771
摘要： A system and method for predictive abnormal behavior detection is disclosed. The system receives surveillance data such as video data and can create and update a plurality of prediction models. The system may also receive video data relating to a moving object and may generate a prediction of the future locations of the moving object based on the generated prediction models. The predicted motion may be scored by a scoring engine to determine if the predicted motion is unsafe or otherwise undesirable.
摘要翻译：公开了一种用于预测性异常行为检测的系统和方法。该系统接收诸如视频数据的监控数据，并且可以创建和更新多个预测模型。该系统还可以接收与移动对象相关的视频数据，并且可以基于所生成的预测模型生成运动对象的未来位置的预测。预测的运动可以由评分引擎评分，以确定预测的运动是不安全的还是不希望的。

8. 发明申请

US20100207762A1 SYSTEM AND METHOD FOR PREDICTING ABNORMAL BEHAVIOR 有权
标题翻译：用于预测异常行为的系统和方法
公开(公告)号：US20100207762A1
公开(公告)日：2010-08-19
申请号：US12496724
申请日：2009-07-02
申请人： Kuo Chu LEE , Hasan Timucin Ozdemir , Juan Yu
发明人： Kuo Chu LEE , Hasan Timucin Ozdemir , Juan Yu
IPC分类号： G08B13/00 , G06F15/18 , G06K9/00 , G06N5/02
CPC分类号： G06K9/00771
摘要： A system and method for predictive abnormal behavior detection is disclosed. The system receives surveillance data such as video data and can create and update a plurality of prediction models. The system may also receive video data relating to a moving object and may generate a prediction of the future locations of the moving object based on the generated prediction models. The predicted motion may be scored by a scoring engine to determine if the predicted motion is unsafe or otherwise undesirable.
摘要翻译：公开了一种用于预测性异常行为检测的系统和方法。该系统接收诸如视频数据的监控数据，并且可以创建和更新多个预测模型。该系统还可以接收与移动对象相关的视频数据，并且可以基于所生成的预测模型生成运动对象的未来位置的预测。预测的运动可以由评分引擎评分，以确定预测的运动是不安全的还是不希望的。

9. 发明申请

US20090210373A1 SYSTEM ARCHITECTURE AND PROCESS FOR SEAMLESS ADAPTATION TO CONTEXT AWARE BEHAVIOR MODELS 有权
标题翻译：系统架构和无缝适应过程以突出特征行为模型
公开(公告)号：US20090210373A1
公开(公告)日：2009-08-20
申请号：US12034164
申请日：2008-02-20
申请人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee
发明人： Juan Yu , Hasan Timucin Ozdemir , Kuo Chu Lee
IPC分类号： G06N5/02
CPC分类号： G06K9/00771 , A61B5/1128 , A61B5/16 , A61B5/7267 , G06K9/00785
摘要： A surveillance system implements an architecture and process to support real-time abnormal behavior assessment operations in a distributed scalable sensor network. An automated behavior model builder generates behavior models from sensor data. A plurality of abnormal behavior scoring engines operating concurrently to generate abnormal behavior assessment models by scoring the behavior models. An execution performance manager performs fast switching of behavior models for the abnormal behavior scoring engines. The execution performance manager performs detection of abnormal behavior score distribution characteristic deviation by comparing a current abnormal behavior assessment model to a pre-recorded abnormal behavior assessment model. The execution performance manager selects a pre-recorded behavior model for the abnormal behavior scoring engines when the deviation exceeds a predetermined threshold.
摘要翻译：监控系统实现一种架构和过程，以支持分布式可扩展传感器网络中的实时异常行为评估操作。自动行为模型构建器从传感器数据生成行为模型。多个异常行为评分引擎同时运行，通过评分行为模型来产生异常行为评估模型。执行性能管理员可以快速切换异常行为评分引擎的行为模型。执行绩效管理者通过将当前的异常行为评估模型与预先记录的异常行为评估模型进行比较来执行异常行为评分分布特征偏差的检测。当偏差超过预定阈值时，执行性能管理器为异常行为评分引擎选择预先记录的行为模型。

10. 发明申请

US20080201116A1 SURVEILLANCE SYSTEM AND METHODS 有权
标题翻译：监督制度与方法
公开(公告)号：US20080201116A1
公开(公告)日：2008-08-21
申请号：US11676127
申请日：2007-02-16
申请人： Hasan Timucin OZDEMIR , Sameer Kibey , Lipin Liu , Kuo Chu Lee , Supraja Mosali , Namsoo Joo , Hongbing Li , Juan Yu
发明人： Hasan Timucin OZDEMIR , Sameer Kibey , Lipin Liu , Kuo Chu Lee , Supraja Mosali , Namsoo Joo , Hongbing Li , Juan Yu
IPC分类号： G06F7/60
CPC分类号： G08B31/00 , G08B13/196 , G08B21/0423
摘要： A surveillance system generally includes a data capture module that collects sensor data. A scoring engine module receives the sensor data and computes at least one of an abnormality score and a normalcy score based on the sensor data, at least one dynamically loaded learned data model, and a learned scoring method. A decision making module receives the at least one of the abnormality score and the normalcy score and generates an alert message based on the at least one of the abnormality score and the normalcy score and a learned decision making method to produce progressive behavior and threat detection.
摘要翻译：监视系统通常包括收集传感器数据的数据捕获模块。评分引擎模块接收传感器数据，并基于传感器数据，至少一个动态加载的学习数据模型和学习评分方法来计算异常分数和正常分数中的至少一个。决策模块接收异常分数和正常分数中的至少一个，并且基于异常得分和正常分数中的至少一个产生警报消息，以及学习决策方法来产生渐进行为和威胁检测。

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