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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。
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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。
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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。
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公开(公告)号:US20110043689A1
公开(公告)日:2011-02-24
申请号:US12543281
申请日:2009-08-18
申请人: Wesley Kenneth Cobb , Dennis Gene Urech , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Tao Yang , Lon William Risinger
发明人: Wesley Kenneth Cobb , Dennis Gene Urech , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Tao Yang , Lon William Risinger
CPC分类号: H04N5/275 , G06K9/00765 , G06T7/246 , G06T2207/10016 , H04N5/147
摘要: Techniques are disclosed for detecting a field-of-view change for a video feed. These techniques differentiate between a new or changed scene and a temporary variation in the scene to accurately detect field-of-view changes for the video feed. A field-of-view change is detected when the position of a camera providing the video feed changes, the video feed is switched to a different camera, the video feed is disconnected, or the camera providing the video feed is obscured. A false-positive field-of-view change is not detected when the scene changes due to a sudden variation in illumination, obstruction of a portion of the camera providing the video feed, blurred images due to an out-of-focus camera, or a transition between bright and dark light when the video feed transitions between color and near infrared capture modes.
摘要翻译: 公开了用于检测视频馈送的视场改变的技术。 这些技术区分新的或改变的场景和场景中的临时变化,以准确地检测视频馈送的视场变化。 当提供视频馈送的相机的位置改变,视频馈送被切换到不同的相机,视频馈送被断开或提供视频馈送的相机被遮蔽时,检测到视野改变。 当场景由于照明的突然变化,提供视频馈送的摄像机的一部分的阻塞,由于离焦照相机引起的模糊图像而变化时,不会检测到假阳性视场改变,或 视频馈送在彩色和近红外捕获模式之间转换时,亮光和暗光之间的转换。
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公开(公告)号:US20110043625A1
公开(公告)日:2011-02-24
申请号:US12543223
申请日:2009-08-18
申请人: Wesley Kenneth Cobb , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Gang Xu , Tao Yang
发明人: Wesley Kenneth Cobb , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Gang Xu , Tao Yang
CPC分类号: G06K9/00771 , G06T7/254 , G06T2207/20081 , G06T2207/30232
摘要: Techniques are disclosed for matching a current background scene of an image received by a surveillance system with a gallery of scene presets that each represent a previously captured background scene. A quadtree decomposition analysis is used to improve the robustness of the matching operation when the scene lighting changes (including portions containing over-saturation/under-saturation) or a portion of the content changes. The current background scene is processed to generate a quadtree decomposition including a plurality of window portions. Each of the window portions is processed to generate a plurality of phase spectra. The phase spectra are then projected onto a corresponding plurality of scene preset image matrices of one or more scene preset. When a match between the current background scene and one of the scene presets is identified, the matched scene preset is updated. Otherwise a new scene preset is created based on the current background scene.
摘要翻译: 公开了用于将由监视系统接收的图像的当前背景场景与每个表示先前捕获的背景场景的场景预设画廊进行匹配的技术。 当场景照明改变(包括包含过饱和/欠饱和的部分)或内容的一部分改变时,使用四叉树分解分析来提高匹配操作的鲁棒性。 处理当前背景场景以产生包括多个窗口部分的四叉树分解。 每个窗口部分被处理以产生多个相位谱。 然后将相位谱投影到一个或多个场景预设的相应的多个场景预设图像矩阵上。 当当前背景场景与其中一个场景预设之间的匹配被识别时,匹配的场景预设被更新。 否则,将根据当前的背景场景创建一个新的场景预设。
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公开(公告)号:US20090087027A1
公开(公告)日:2009-04-02
申请号:US12208526
申请日:2008-09-11
申请人: John Eric Eaton , Wesley Kenneth Cobb , Rajkiran Kumar Gottumukkal , Ming-Jung Seow , Tao Yang , Kishor Adinath Saitwal
发明人: John Eric Eaton , Wesley Kenneth Cobb , Rajkiran Kumar Gottumukkal , Ming-Jung Seow , Tao Yang , Kishor Adinath Saitwal
IPC分类号: G06F15/18
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。
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公开(公告)号:US09805271B2
公开(公告)日:2017-10-31
申请号:US12543223
申请日:2009-08-18
申请人: Wesley Kenneth Cobb , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Gang Xu , Tao Yang
发明人: Wesley Kenneth Cobb , Bobby Ernest Blythe , Rajkiran Kumar Gottumukkal , Kishor Adinath Saitwal , Gang Xu , Tao Yang
CPC分类号: G06K9/00771 , G06T7/254 , G06T2207/20081 , G06T2207/30232
摘要: Techniques are disclosed for matching a current background scene of an image received by a surveillance system with a gallery of scene presets that each represent a previously captured background scene. A quadtree decomposition analysis is used to improve the robustness of the matching operation when the scene lighting changes (including portions containing over-saturation/under-saturation) or a portion of the content changes. The current background scene is processed to generate a quadtree decomposition including a plurality of window portions. Each of the window portions is processed to generate a plurality of phase spectra. The phase spectra are then projected onto a corresponding plurality of scene preset image matrices of one or more scene preset. When a match between the current background scene and one of the scene presets is identified, the matched scene preset is updated. Otherwise a new scene preset is created based on the current background scene.
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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
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。
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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
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。
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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。
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