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    GROUPING ITEMS IN VIDEO STREAM IMAGES INTO EVENTS
    2.
    发明申请
    GROUPING ITEMS IN VIDEO STREAM IMAGES INTO EVENTS 有权
    将视频流图像中的项目分组到事件中

    公开(公告)号：US20100080492A1

    公开(公告)日：2010-04-01

    申请号：US12632726

    申请日：2009-12-07

    申请人： Gordon T. Haupt ,  J. Andrew Freeman ,  Stephen D. Fleischer ,  Robert P. Vallone ,  Stephen G. Russell ,  Timothy B. Frederick

    发明人： Gordon T. Haupt ,  J. Andrew Freeman ,  Stephen D. Fleischer ,  Robert P. Vallone ,  Stephen G. Russell ,  Timothy B. Frederick

    IPC分类号： G06K9/54

    CPC分类号： G06K9/00295

    摘要： A technique is disclosed for determining when to close a group of a plurality of groups. A closed group is one to which an image set may not be added. Each group includes one or more image sets. Each image set includes one or more images of at least one object. Each group corresponds to an object that is common among images in the one or more image sets that belong to the group. Determining when to close a particular group is based, at least in part, on one or more factors, such as how many image sets are in the particular group, the length of time the particular group has been open, and data about the one or more image sets in the particular group.

    摘要翻译： 公开了一种用于确定何时关闭多个组的组的技术。 封闭的组是不能添加图像集的组。 每个组包括一个或多个图像组。 每个图像集合包括至少一个对象的一个​​或多个图像。 每个组对应于属于该组的一个或多个图像集合中的图像中常见的对象。 至少部分地基于一个或多个因素来确定什么时候关闭特定的组，例如特定组中有多少个图像组，特定组已经打开的时间长度以及关于该组的数据 特定组中的更多图像集。

    Grouping items in video stream images into events
    6.
    发明授权
    Grouping items in video stream images into events 有权
    将视频流图像中的项目分组到事件中

    公开(公告)号：US07933455B2

    公开(公告)日：2011-04-26

    申请号：US12632726

    申请日：2009-12-07

    申请人： Gordon T. Haupt ,  J. Andrew Freeman ,  Stephen D. Fleischer ,  Robert P. Vallone ,  Stephen G. Russell ,  Timothy B. Frederick

    发明人： Gordon T. Haupt ,  J. Andrew Freeman ,  Stephen D. Fleischer ,  Robert P. Vallone ,  Stephen G. Russell ,  Timothy B. Frederick

    IPC分类号： G06K9/62 ,  G06K9/00

    CPC分类号： G06K9/00295

    摘要： A technique is disclosed for determining when to close a group of a plurality of groups. A closed group is one to which an image set may not be added. Each group includes one or more image sets. Each image set includes one or more images of at least one object. Each group corresponds to an object that is common among images in the one or more image sets that belong to the group. Determining when to close a particular group is based, at least in part, on one or more factors, such as how many image sets are in the particular group, the length of time the particular group has been open, and data about the one or more image sets in the particular group.

    摘要翻译： 公开了一种用于确定何时关闭一组多个组的技术。 封闭的组是不能添加图像集的组。 每个组包括一个或多个图像组。 每个图像集合包括至少一个对象的一个​​或多个图像。 每个组对应于属于该组的一个或多个图像集中的图像中常见的对象。 至少部分地基于一个或多个因素来确定什么时候关闭特定的组，例如特定组中有多少个图像组，特定组已经打开的时间长度以及关于该组的数据 特定组中的更多图像集。

    Event generation and camera cluster analysis of multiple video streams in a pipeline architecture
    8.
    发明授权
    Event generation and camera cluster analysis of multiple video streams in a pipeline architecture 有权
    在流水线架构中的多个视频流的事件生成和相机聚类分析

    公开(公告)号：US07667732B1

    公开(公告)日：2010-02-23

    申请号：US10965676

    申请日：2004-10-13

    申请人： J. Andrew Freeman ,  Robert P. Vallone ,  Stephen G. Russell ,  Christian Pappas ,  Stephen D. Fleischer ,  Gordon T. Haupt

    发明人： J. Andrew Freeman ,  Robert P. Vallone ,  Stephen G. Russell ,  Christian Pappas ,  Stephen D. Fleischer ,  Gordon T. Haupt

    IPC分类号： H04N7/18

    CPC分类号： G06K9/00973 ,  G06K9/00711 ,  G08B13/19671

    摘要： A pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.

    摘要翻译： 用于分析多个视频流的流水线架构部分地体现在每个处理阶段的应用程序接口（API）层中。 在一些阶段之间使用缓冲区排队，这有助于缓和CPU上的负载。 通过API层，无数的视频分析应用程序可以访问和分析流经流水线的视频数据，并且可以基于所执行的分析来注释视频数据的一部分（例如，帧和帧组），其中描述 框架或组。 这些注释的帧和组流经管线到处理的后续阶段，在该阶段可以执行越来越复杂的分析。 在每个阶段，从视频数据中删除少量或不感兴趣的视频数据的部分。 最终，“事件”被构建并存储在数据库中，可以从该数据库中进行交叉事件和历史分析，并且可以进行与事件的关联以及事件之间的关联。

    Feed-customized processing of multiple video streams in a pipeline architecture
    9.
    发明授权
    Feed-customized processing of multiple video streams in a pipeline architecture 有权
    在流水线架构中对多个视频流进行自定义处理

    公开(公告)号：US07663661B2

    公开(公告)日：2010-02-16

    申请号：US10964977

    申请日：2004-10-13

    申请人： Robert P. Vallone ,  J. Andrew Freeman ,  Stephen G. Russell ,  Thomas W. Kirkman ,  Stephen D. Fleischer ,  Gordon T. Haupt

    发明人： Robert P. Vallone ,  J. Andrew Freeman ,  Stephen G. Russell ,  Thomas W. Kirkman ,  Stephen D. Fleischer ,  Gordon T. Haupt

    IPC分类号： H04N7/18

    CPC分类号： H04N7/181 ,  G06K9/00711 ,  G06K9/00986

    摘要： A pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.

    摘要翻译： 用于分析多个视频流的流水线架构部分地体现在每个处理阶段的应用程序接口（API）层中。 在一些阶段之间使用缓冲区排队，这有助于缓和CPU上的负载。 通过API层，无数视频分析应用程序可以访问和分析流经流水线的视频数据，并且可以基于所执行的分析来注释视频数据的一部分（例如，帧和帧组），其中描述 框架或组。 这些注释的帧和组流经管线到处理的后续阶段，在该阶段可以执行越来越复杂的分析。 在每个阶段，从视频数据中删除少量或不感兴趣的视频数据的部分。 最终，“事件”被构建并存储在数据库中，可以从该数据库中进行交叉事件和历史分析，并且可以进行与事件的关联以及事件之间的关联。

    Deep frame analysis of multiple video streams in a pipeline architecture
    10.
    发明授权
    Deep frame analysis of multiple video streams in a pipeline architecture 有权
    在流水线架构中的多个视频流的深度帧分析

    公开(公告)号：US07672370B1

    公开(公告)日：2010-03-02

    申请号：US10965682

    申请日：2004-10-13

    申请人： Stephen G. Russell ,  J. Andrew Freeman ,  Robert P. Vallone ,  Christian Pappas ,  Stephen D. Fleischer ,  Gordon T. Haupt

    发明人： Stephen G. Russell ,  J. Andrew Freeman ,  Robert P. Vallone ,  Christian Pappas ,  Stephen D. Fleischer ,  Gordon T. Haupt

    IPC分类号： H04B1/66

    CPC分类号： G06K9/00973 ,  G06K9/00711 ,  G08B13/19671

    摘要： A pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.

    摘要翻译： 用于分析多个视频流的流水线架构部分地体现在每个处理阶段的应用程序接口（API）层中。 在一些阶段之间使用缓冲区排队，这有助于缓和CPU上的负载。 通过API层，无数的视频分析应用程序可以访问和分析流经流水线的视频数据，并且可以基于所执行的分析来注释视频数据的一部分（例如，帧和帧组），其中描述 框架或组。 这些注释的帧和组流经管线到处理的后续阶段，在该阶段可以执行越来越复杂的分析。 在每个阶段，从视频数据中删除少量或不感兴趣的视频数据的部分。 最终，“事件”被构建并存储在数据库中，可以从该数据库中进行交叉事件和历史分析，并且可以进行与事件的关联以及事件之间的关联。