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11. 发明授权

US08218819B2 Foreground object detection in a video surveillance system 有权
标题翻译：视频监控系统中的前景物体检测
公开(公告)号：US08218819B2
公开(公告)日：2012-07-10
申请号：US12552210
申请日：2009-09-01
申请人： Wesley Kenneth Cobb , Ming-Jung Seow , Tao Yang
发明人： Wesley Kenneth Cobb , Ming-Jung Seow , Tao Yang
IPC分类号： G06K9/00
CPC分类号： G06K9/00771 , G06T7/215 , G06T7/254 , G06T2207/10016 , G06T2207/30196 , G06T2207/30232 , G06T2207/30236 , G06T2207/30241 , G08B13/19608
摘要： Techniques are disclosed for detecting foreground objects in a scene captured by a surveillance system and tracking the detected foreground objects from frame to frame in real time. A motion flow field is used to validate foreground objects(s) that are extracted from the background model of a scene. Spurious foreground objects are filtered before the detected foreground objects are provided to the tracking stage. The motion flow field is also used by the tracking stage to improve the performance of the tracking as needed for real time surveillance applications.
摘要翻译：公开了用于检测由监视系统捕获的场景中的前景物体并且实时地从帧到帧跟踪检测到的前景物体的技术。运动流场用于验证从场景的背景模型中提取的前景对象。在检测到的前景对象提供给跟踪阶段之前，会对前景对象进行过滤。跟踪阶段还使用运动流场来提高实时监控应用所需的跟踪性能。

12. 发明授权

US08189905B2 Cognitive model for a machine-learning engine in a video analysis system 有权
标题翻译：视频分析系统中机器学习引擎的认知模型
公开(公告)号：US08189905B2
公开(公告)日：2012-05-29
申请号：US12170283
申请日：2008-07-09
申请人： John Eric Eaton , Wesley Kenneth Cobb , Dennis G. Urech , David S. Friedlander , Gang Xu , Ming-Jung Seow , Lon W. Risinger , David M. Solum , Tao Yang , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal
发明人： John Eric Eaton , Wesley Kenneth Cobb , Dennis G. Urech , David S. Friedlander , Gang Xu , Ming-Jung Seow , Lon W. Risinger , David M. Solum , Tao Yang , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal
IPC分类号： G06K9/62 , 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.
摘要翻译：公开了一种机器学习引擎，其被配置为通过随时间分析移动和/或活动（或不存在）来识别和学习行为，以及识别和区分场景内的正常和异常行为。机器学习引擎可以被配置为评估为视频帧序列和相关向量表示中描绘的对象生成的原始事件序列和相关联的运动学数据序列。从原始事件符号流和相位空间符号流生成向量表示，并且流描述在视频帧序列中描绘的对象的动作。

13. 发明授权

US08175333B2 Estimator identifier component for behavioral recognition system 有权
标题翻译：用于行为识别系统的估计器标识符组件
公开(公告)号：US08175333B2
公开(公告)日：2012-05-08
申请号：US12208526
申请日：2008-09-11
申请人： John Eric Eaton , Wesley Kenneth Cobb , Rajkiran K. Gottumukkal , Ming-Jung Seow , Tao Yang , Kishor Adinath Saitwal
发明人： John Eric Eaton , Wesley Kenneth Cobb , Rajkiran K. Gottumukkal , Ming-Jung Seow , Tao Yang , Kishor Adinath Saitwal
IPC分类号： G06K9/00
CPC分类号： G06F15/16
摘要： An estimator/identifier component for a computer vision engine of a machine-learning based behavior-recognition system is disclosed. The estimator/identifier component may be configured to classify an object being one of two or more classification types, e.g., as being a vehicle or a person. Once classified, the estimator/identifier may evaluate the object to determine a set of kinematic data, static data, and a current pose of the object. The output of the estimator/identifier component may include the classifications assigned to a tracked object, as well as the derived information and object attributes.
摘要翻译：公开了一种基于机器学习的行为识别系统的计算机视觉引擎的估计/标识符组件。估计器/标识符组件可以被配置为将作为两个或更多个分类类型之一的对象进行分类，例如，作为车辆或人。一旦分类，估计器/标识符可以评估对象以确定一组运动学数据，静态数据和对象的当前姿态。估计器/标识符组件的输出可以包括分配给跟踪对象的分类以及派生的信息和对象属性。

14. 发明授权

US08131012B2 Behavioral recognition system 有权
标题翻译：行为识别系统
公开(公告)号：US08131012B2
公开(公告)日：2012-03-06
申请号：US12028484
申请日：2008-02-08
申请人： John Eric Eaton , Wesley Kenneth Cobb , Dennis Gene Urech , Bobby Ernest Blythe , David Samuel Friedlander , Rajkiran Kumar Gottumukkal , Lon William Risinger , Kishor Adinath Saitwal , Ming-Jung Seow , David Marvin Solum , Gang Xu , Tao Yang
发明人： John Eric Eaton , Wesley Kenneth Cobb , Dennis Gene Urech , Bobby Ernest Blythe , David Samuel Friedlander , Rajkiran Kumar Gottumukkal , Lon William Risinger , Kishor Adinath Saitwal , Ming-Jung Seow , David Marvin Solum , Gang Xu , Tao Yang
IPC分类号： G06K9/00
CPC分类号： G06K9/00771 , G08B13/19608 , G08B13/19613
摘要： Embodiments of the present invention provide a method and a system for analyzing and learning behavior based on an acquired stream of video frames. Objects depicted in the stream are determined based on an analysis of the video frames. Each object may have a corresponding search model used to track an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.
摘要翻译：本发明的实施例提供了一种基于所获取的视频帧流来分析和学习行为的方法和系统。基于对视频帧的分析来确定流中描绘的对象。每个对象可以具有用于跟踪对象的帧到帧的运动的对应的搜索模型。确定对象的类，并生成对象的语义表示。语义表示用于确定对象的行为，并了解在所获取的视频流中描绘的环境中发生的行为。通过这种方式，系统通过分析环境中的动作或活动或不存在这些环境，快速，实时地对任何环境的正常和异常行为进行学习，并根据所学到的知识和预测异常和可疑行为。

15. 发明授权

US08094943B2 Background-foreground module for video analysis system 有权
标题翻译：视频分析系统的背景前景模块
公开(公告)号：US08094943B2
公开(公告)日：2012-01-10
申请号：US12129521
申请日：2008-05-29
申请人： John Eric Eaton , Wesley Kenneth Cobb , Bobby Ernest Blythe , Kishor Adinath Saitwal , Tao Yang , Ming-Jung Seow
发明人： John Eric Eaton , Wesley Kenneth Cobb , Bobby Ernest Blythe , Kishor Adinath Saitwal , Tao Yang , Ming-Jung Seow
IPC分类号： G06K9/46 , G06K9/62 , G06K9/00
CPC分类号： G06K9/38
摘要： Embodiments of the present invention provide a method and a module for identifying a background of a scene depicted in an acquired stream of video frames that may be used by a video-analysis system. For each pixel or block of pixels in an acquired video frame a comparison measure is determined. The comparison measure depends on difference of color values exhibited in the acquired video frame and in a background image respectively by the pixel or block of pixels and a corresponding pixel and block of pixels in the background image. To determine the comparison measure, the resulting difference is considered in relation to a range of possible color values. If the comparison measure is above a dynamically adjusted threshold, the pixel or the block of pixels is classified as a part of the background of the scene.
摘要翻译：本发明的实施例提供了一种用于识别视频分析系统可以使用的所获取的视频帧流中描绘的场景的背景的方法和模块。对于所获取的视频帧中的每个像素或像素块，确定比较度量。比较测量取决于所获取的视频帧和背景图像中分别由像素或像素块以及背景图像中的对应像素和像素块显示的颜色值的差异。为了确定比较测量，考虑到与可能的颜色值的范围的差异。如果比较度量高于动态调整的阈值，像素或像素块被分类为场景背景的一部分。

16. 发明申请

US20110052002A1 FOREGROUND OBJECT TRACKING 有权
标题翻译：前缀对象跟踪
公开(公告)号：US20110052002A1
公开(公告)日：2011-03-03
申请号：US12552197
申请日：2009-09-01
申请人： WESLEY KENNETH COBB , Ming-Jung Seow , Tao Yang
发明人： WESLEY KENNETH COBB , Ming-Jung Seow , Tao Yang
IPC分类号： G06K9/00
CPC分类号： G06K9/00771 , G06T7/215 , G06T7/254 , G06T2207/10016 , G06T2207/30196 , G06T2207/30236 , G06T2207/30241 , G08B13/19608
摘要： Techniques are disclosed for detecting foreground objects in a scene captured by a surveillance system and tracking the detected foreground objects from frame to frame in real time. A motion flow field is used to validate foreground objects(s) that are extracted from the background model of a scene. Spurious foreground objects are filtered before the foreground objects are provided to the tracking stage. The motion flow field is also used by the tracking stage to improve the performance of the tracking as needed for real time surveillance applications.
摘要翻译：公开了用于检测由监视系统捕获的场景中的前景物体并且实时地从帧到帧跟踪检测到的前景物体的技术。运动流场用于验证从场景的背景模型中提取的前景对象。在将前景对象提供给跟踪阶段之前，会对前景对象进行过滤。跟踪阶段还使用运动流场来提高实时监控应用所需的跟踪性能。

17. 发明申请

US20110044537A1 BACKGROUND MODEL FOR COMPLEX AND DYNAMIC SCENES 有权
标题翻译：复杂和动态场景的背景模型
公开(公告)号：US20110044537A1
公开(公告)日：2011-02-24
申请号：US12543336
申请日：2009-08-18
申请人： Wesley Kenneth Cobb , Ming-Jung Seow , Tao Yang
发明人： Wesley Kenneth Cobb , Ming-Jung Seow , Tao Yang
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06T7/20 , G06K9/00335 , G06K9/00718 , G06K9/00771 , G06K9/6218 , G06K9/6222 , G06K9/66 , G06K2009/00738 , G06T7/254 , G06T2207/10016 , G06T2207/20084 , G06T2207/30196 , G06T2207/30232
摘要： Techniques are disclosed for learning and modeling a background for a complex and/or dynamic scene over a period of observations without supervision. A background/foreground component of a computer vision engine may be configured to model a scene using an array of ART networks. The ART networks learn the regularity and periodicity of the scene by observing the scene over a period of time. Thus, the ART networks allow the computer vision engine to model complex and dynamic scene backgrounds in video.
摘要翻译：披露了一种技术，用于在无监督的一段时间内为复杂和/或动态场景学习和建模背景。计算机视觉引擎的背景/前景分量可以被配置为使用ART网络阵列对场景建模。 ART网络通过观察一段时间内的场景，了解场景的规律性和周期性。因此，ART网络允许计算机视觉引擎在视频中对复杂和动态的场景背景进行建模。

18. 发明申请

US20090087096A1 BACKGROUND-FOREGROUND MODULE FOR VIDEO ANALYSIS SYSTEM 有权
标题翻译：视频分析系统背景模块
公开(公告)号：US20090087096A1
公开(公告)日：2009-04-02
申请号：US12129521
申请日：2008-05-29
申请人： John Eric Eaton , Wesley Kenneth Cobb , Bobby Ernest Blythe , Kishor Adinath Saitwal , Tao Yang , Ming-Jung Seow
发明人： John Eric Eaton , Wesley Kenneth Cobb , Bobby Ernest Blythe , Kishor Adinath Saitwal , Tao Yang , Ming-Jung Seow
IPC分类号： G06K9/46 , G06K9/62
CPC分类号： G06K9/38
摘要： Embodiments of the present invention provide a method and a module for identifying a background of a scene depicted in an acquired stream of video frames that may be used by a video-analysis system. For each pixel or block of pixels in an acquired video frame a comparison measure is determined. The comparison measure depends on difference of color values exhibited in the acquired video frame and in a background image respectively by the pixel or block of pixels and a corresponding pixel and block of pixels in the background image. To determine the comparison measure, the resulting difference is considered in relation to a range of possible color values. If the comparison measure is above a dynamically adjusted threshold, the pixel or the block of pixels is classified as a part of the background of the scene.
摘要翻译：本发明的实施例提供了一种用于识别视频分析系统可以使用的所获取的视频帧流中描绘的场景的背景的方法和模块。对于所获取的视频帧中的每个像素或像素块，确定比较度量。比较测量取决于所获取的视频帧和背景图像中分别由像素或像素块以及背景图像中的对应像素和像素块显示的颜色值的差异。为了确定比较测量，考虑到与可能的颜色值的范围的差异。如果比较度量高于动态调整的阈值，像素或像素块被分类为场景背景的一部分。

19. 发明申请

US20090016600A1 COGNITIVE MODEL FOR A MACHINE-LEARNING ENGINE IN A VIDEO ANALYSIS SYSTEM 有权
标题翻译：视频分析系统中机器学习发动机的认知模型
公开(公告)号：US20090016600A1
公开(公告)日：2009-01-15
申请号：US12170283
申请日：2008-07-09
申请人： JOHN ERIC EATON , Wesley Kenneth Cobb , Dennis G. Urech , David S. Friedlander , Gang Xu , Ming-Jung Seow , Lon W. Risinger , David M. Solum , Tao Yang , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal
发明人： JOHN ERIC EATON , Wesley Kenneth Cobb , Dennis G. Urech , David S. Friedlander , Gang Xu , Ming-Jung Seow , Lon W. Risinger , David M. Solum , Tao Yang , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal
IPC分类号： G06K9/62 , G06K9/00 , G06F15/18
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.
摘要翻译：公开了一种机器学习引擎，其被配置为通过随时间分析移动和/或活动（或不存在）来识别和学习行为，以及识别和区分场景内的正常和异常行为。机器学习引擎可以被配置为评估为视频帧序列和相关向量表示中描绘的对象生成的原始事件序列和相关联的运动学数据序列。从原始事件符号流和相位空间符号流生成向量表示，并且流描述在视频帧序列中描绘的对象的动作。

20. 发明授权

US08285046B2 Adaptive update of background pixel thresholds using sudden illumination change detection 有权
标题翻译：使用突然照明变化检测自适应更新背景像素阈值
公开(公告)号：US08285046B2
公开(公告)日：2012-10-09
申请号：US12388409
申请日：2009-02-18
申请人： Wesley Kenneth Cobb , Kishor Adinath Saitwal , Bobby Ernest Blythe , Tao Yang
发明人： Wesley Kenneth Cobb , Kishor Adinath Saitwal , Bobby Ernest Blythe , Tao Yang
IPC分类号： G06K9/34
CPC分类号： G06K9/00771
摘要： Techniques are disclosed for a computer vision engine to update both a background model and thresholds used to classify pixels as depicting scene foreground or background in response to detecting that a sudden illumination changes has occurred in a sequence of video frames. The threshold values may be used to specify how much pixel a given pixel may differ from corresponding values in the background model before being classified as depicting foreground. When a sudden illumination change is detected, the values for pixels affected by sudden illumination change may be used to update the value in the background image to reflect the value for that pixel following the sudden illumination change as well as update the threshold for classifying that pixel as depicting foreground/background in subsequent frames of video.
摘要翻译：公开了用于计算机视觉引擎的技术，用于更新背景模型和用于将像素分类为描绘场景前景或背景的阈值，以响应于检测到在视频帧序列中已经发生突然的照明变化。可以使用阈值来指定给定像素在分类为描绘前景之前可能与背景模型中的对应值不同的像素。当检测到突然的照明变化时，可以使用受突然照明改变影响的像素的值来更新背景图像中的值，以反映在突然照射变化之后该像素的值，并且更新用于对该像素进行分类的阈值作为描绘后续视频帧中的前景/背景。

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