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。

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。

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。

公开(公告)号：US08620028B2

公开(公告)日：2013-12-31

申请号：US13413549

申请日：2012-03-06

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： G06K9/62

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。

公开(公告)号：US08300924B2

公开(公告)日：2012-10-30

申请号：US12208538

申请日：2008-09-11

申请人： John Eric Eaton ,  Wesley Kenneth Cobb ,  Rajkiran K. Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Tao Yang ,  Bobby Ernest Blythe

发明人： John Eric Eaton ,  Wesley Kenneth Cobb ,  Rajkiran K. Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Tao Yang ,  Bobby Ernest Blythe

IPC分类号： G06K9/62

CPC分类号： G06F15/16

摘要： A tracker component for a computer vision engine of a machine-learning based behavior-recognition system is disclosed. The behavior-recognition system may be configured to learn, identify, and recognize patterns of behavior by observing a video stream (i.e., a sequence of individual video frames). The tracker component may be configured to track objects depicted in the sequence of video frames and to generate, search, match, and update computational models of such objects.

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跟踪器组件。 行为识别系统可以被配置为通过观察视频流（即，各个视频帧的序列）来学习，识别和识别行为模式。 跟踪器组件可以被配置为跟踪视频帧序列中描绘的对象并且生成，搜索，匹配和更新这些对象的计算模型。

公开(公告)号：US20080193010A1

公开(公告)日：2008-08-14

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： G06F15/18

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。

公开(公告)号：US08797405B2

公开(公告)日：2014-08-05

申请号：US12551332

申请日：2009-08-31

申请人： Wesley Kenneth Cobb ,  Bobby Ernest Blythe ,  David Samuel Friedlander ,  Rajkiran Kumar Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Gang Xu

发明人： Wesley Kenneth Cobb ,  Bobby Ernest Blythe ,  David Samuel Friedlander ,  Rajkiran Kumar Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Gang Xu

IPC分类号： H04N7/18 ,  G06K9/00

CPC分类号： G06K9/00771 ,  G06K9/00973

摘要： Techniques are disclosed for visually conveying classifications derived from pixel-level micro-features extracted from image data. The image data may include an input stream of video frames depicting one or more foreground objects. The classifications represent information learned by a video surveillance system. A request may be received to view a classification. A visual representation of the classification may be generated. A user interface may be configured to display the visual representation of the classification and to allow a user to view and/or modify properties associated with the classification.

摘要翻译： 公开了用于视觉地传送从图像数据提取的像素级微特征得出的分类的技术。 图像数据可以包括描绘一个或多个前景对象的视频帧的输入流。 分类表示视频监控系统学到的信息。 可以接收到查看分类的请求。 可以生成分类的视觉表示。 用户界面可以被配置为显示分类的可视表示，并允许用户查看和/或修改与分类相关联的属性。

公开(公告)号：US20110050897A1

公开(公告)日：2011-03-03

申请号：US12551332

申请日：2009-08-31

申请人： Wesley Kenneth Cobb ,  Bobby Ernest Blythe ,  David Samuel Friedlander ,  Rajkiran Kumar Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Gang Xu

发明人： Wesley Kenneth Cobb ,  Bobby Ernest Blythe ,  David Samuel Friedlander ,  Rajkiran Kumar Gottumukkal ,  Kishor Adinath Saitwal ,  Ming-Jung Seow ,  Gang Xu

IPC分类号： H04N7/16

CPC分类号： G06K9/00771 ,  G06K9/00973

摘要： Techniques are disclosed for visually conveying classifications derived from pixel-level micro-features extracted from image data. The image data may include an input stream of video frames depicting one or more foreground objects. The classifications represent information learned by a video surveillance system. A request may be received to view a classification. A visual representation of the classification may be generated. A user interface may be configured to display the visual representation of the classification and to allow a user to view and/or modify properties associated with the classification.

摘要翻译： 公开了用于视觉地传送从图像数据提取的像素级微特征得出的分类的技术。 图像数据可以包括描绘一个或多个前景对象的视频帧的输入流。 分类表示视频监控系统学到的信息。 可能会收到请求以查看分类。 可以生成分类的视觉表示。 用户界面可以被配置为显示分类的可视表示，并允许用户查看和/或修改与分类相关联的属性。

公开(公告)号：US20090087085A1

公开(公告)日：2009-04-02

申请号：US12208538

申请日：2008-09-11

申请人： JOHN ERIC EATON ,  Wesley Kenneth Cobb ,  Rajkiran K. Gottumukkal ,  Kishore Adinath Saitwal ,  Ming-Jung Seow ,  Tao Yang ,  Bobby Ernest Blythe

发明人： JOHN ERIC EATON ,  Wesley Kenneth Cobb ,  Rajkiran K. Gottumukkal ,  Kishore Adinath Saitwal ,  Ming-Jung Seow ,  Tao Yang ,  Bobby Ernest Blythe

IPC分类号： G06F15/18

CPC分类号： G06F15/16

摘要： A tracker component for a computer vision engine of a machine-learning based behavior-recognition system is disclosed. The behavior-recognition system may be configured to learn, identify, and recognize patterns of behavior by observing a video stream (i.e., a sequence of individual video frames). The tracker component may be configured to track objects depicted in the sequence of video frames and to generate, search, match, and update computational models of such objects.

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跟踪器组件。 行为识别系统可以被配置为通过观察视频流（即，各个视频帧的序列）来学习，识别和识别行为模式。 跟踪器组件可以被配置为跟踪视频帧序列中描绘的对象并且生成，搜索，匹配和更新这些对象的计算模型。

公开(公告)号：US08064695B2

公开(公告)日：2011-11-22

申请号：US12129539

申请日：2008-05-29

申请人： John Eric Eaton ,  Wesley Kenneth Cobb ,  Kishor Adinath Saitwal ,  Bobby Ernest Blythe

发明人： John Eric Eaton ,  Wesley Kenneth Cobb ,  Kishor Adinath Saitwal ,  Bobby Ernest Blythe

IPC分类号： G06K9/34 ,  H04N7/12 ,  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。