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1.发明公开SEMANTIC REPRESENTATION MODULE OF A MACHINE-LEARNING ENGINE IN A VIDEO ANALYSIS SYSTEM 审中-公开在视频分析系统的机器机器学习的语义呈现模块
公开(公告)号：EP2176813A4
公开(公告)日：2015-09-30
申请号：EP08796147
申请日：2008-07-10
发明人： EATON JOHN ERIC , COBB WESLEY KENNETH , URECH DENNIS G , FRIEDLANDER DAVID S , XU GANG , SEOW MING-JUNG , RISINGER LON W , SOLUM DAVID M , YANG TAO , GOTTUMUKKAL RAJKIRAN K , SAITWAL KISHOR ADINATH
IPC分类号： G06K9/62
CPC分类号： G06K9/00718 , G06F17/30598 , G06K9/00335 , G06K9/00751 , G06K9/00771 , G06K9/6215 , G06K9/66 , G06K2009/00738 , G06N99/005
摘要： A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.
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2.发明公开A COGNITIVE NEURO-LINGUISTIC BEHAVIOR RECOGNITION SYSTEM FOR MULTI-SENSOR DATA FUSION 审中-公开用于检测融合多传感器数据的认知神经语言行为的系统
公开(公告)号：EP3030981A4
公开(公告)日：2016-09-07
申请号：EP14833998
申请日：2014-08-11
发明人： SEOW MING-JUNG , COBB WESLEY KENNETH , XU GANG , YANG TAO , POFFENBERGER AARON , RISINGER LON W , SAITWAL KISHOR ADINATH , YANTOSCA MICHAEL S , SOLUM DAVID M , HEMSATH ALEX DAVID , URECH DENNIS G , NGUYEN DUY TRONG , MORGAN CHARLES RICHARD
CPC分类号： H04L63/1425 , G06F17/2725 , G06F17/2735 , G06F17/274 , G06F17/277 , G06F17/2775 , G06F17/2785 , G06F17/2795 , G06F17/28 , G06N99/005 , H04L63/1408
摘要： Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.
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公开(公告)号：EP2342647A4
公开(公告)日：2016-02-24
申请号：EP09813628
申请日：2009-09-10
CPC分类号： G06N99/005 , G06K9/00335 , G06K9/00771 , G06K9/6296
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公开(公告)号：EP2118864A4
公开(公告)日：2012-08-01
申请号：EP08729422
申请日：2008-02-08
发明人： EATON JOHN ERIC , COBB WESLEY KENNETH , URECH DENNIS GENE , BLYTHE BOBBY ERNEST , FRIEDLANDER DAVID SAMUEL , GOTTUMUKKAL RAJKIRAN KUMAR , RISINGER LON WILLIAM , SAITWAL KISHOR ADINATH , SEOW MING-JUNG , SOLUM DAVID MARVIN , XU GANG , YANG TAO
IPC分类号： G08B23/00 , G06K9/00 , G08B13/196 , G08B31/00
CPC分类号： G06K9/00771 , G08B13/19608 , G08B13/19613
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5.发明公开ALERT DIRECTIVES AND FOCUSED ALERT DIRECTIVES IN A BEHAVIORAL RECOGNITION SYSTEM 审中-公开警示说明，重点突出警示说明IN A行为检测系统
公开(公告)号：EP2826029A4
公开(公告)日：2016-10-26
申请号：EP13760772
申请日：2013-03-15
发明人： COBB WESLEY KENNETH , SEOW MING-JUNG , XU GANG , SAITWAL KISHOR ADINATH , AKINS ANTHONY , JOSEPH KERRY , URECH DENNIS
CPC分类号： G08B29/185 , G06K9/00369 , G06K9/00771 , G06K9/00778 , G06K9/3241 , G06K9/52 , G06K9/6254 , G08B13/19608 , G08B21/182 , G08B23/00 , H04N7/002
摘要： A behavioral recognition system may include both a computer vision engine and a machine learning engine configured to observe and learn patterns of behavior in video data. Certain embodiments may be configured to learn patterns of behavior consistent with a person loitering and generate alerts for same. Upon receiving information of a foreground object remaining in a scene over a threshold period of time, a loitering detection module evaluates the whether the object trajectory corresponds to a random walk. Upon determining that the trajectory does correspond, the loitering detection module generates a loitering alert.
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公开(公告)号：EP2473969A4
公开(公告)日：2016-03-23
申请号：EP10812486
申请日：2010-08-11
发明人： COBB WESLEY KENNETH , SEOW MING-JUNG , XU GANG
CPC分类号： G06K9/00771 , G06K9/00335 , G06K9/00718 , G06K9/6284 , G06T7/246 , G06T2207/10016 , G06T2207/10024 , G06T2207/30232 , G06T2207/30241
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7.发明公开
公开(公告)号：EP2176811A4
公开(公告)日：2015-09-30
申请号：EP08781639
申请日：2008-07-10
发明人： EATON JOHN ERIC , COBB WESLEY KENNETH , URECH DENNIS G , FRIEDLANDER DAVID S , XU GANG , SEOW MING-JUNG , RISINGER LON W , SOLUM DAVID M , YANG TAO , GOTTUMUKKAL RAJKIRAN K , SAITWAL KISHOR ADINATH
IPC分类号： G06K9/00
CPC分类号： G06K9/00718 , G06F17/30598 , G06K9/00335 , G06K9/00751 , G06K9/00771 , G06K9/6215 , G06K9/66 , G06K2009/00738 , G06N99/005
摘要： A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.
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8.发明公开DETECTING ANOMALOUS EVENTS USING A LONG-TERM MEMORY IN A VIDEO ANALYSIS SYSTEM 有权异常事件上的长期记忆的基础在视频分析系统检测
公开(公告)号：EP2377044A4
公开(公告)日：2015-02-25
申请号：EP09836911
申请日：2009-12-16
发明人： COBB WESLEY KENNETH , SEOW MING-JUNG , XU GANG
CPC分类号： G06K9/00771 , G06K9/6215
摘要： Techniques are described for detecting anomalous events using a long-term memory in a video analysis system. The long-term memory may be used to store and retrieve information learned while a video analysis system observes a stream of video frames depicting a given scene. Further, the long-term memory may be configured to detect the occurrence of anomalous events, relative to observations of other events that have occurred in the scene over time. A distance measure may used to determine a distance between an active percept (encoding an observed event depicted in the stream of video frames) and a retrieved percept (encoding a memory of previously observed events in the long-term memory). If the distance exceeds a specified threshold, the long-term memory may publish the occurrence of an anomalous event for review by users of the system.
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