Tools for micro-communities
    1.
    发明授权
    Tools for micro-communities 有权
    微社区工具

    公开(公告)号:US08694593B1

    公开(公告)日:2014-04-08

    申请号:US13198569

    申请日:2011-08-04

    IPC分类号: G06F15/16

    CPC分类号: H04L51/32 G06Q50/01 G06Q50/10

    摘要: A system and method for associating users with a micro-community that is relevant to an object reference. The object reference is anything that can be perceived either physically or conceptually, such as a location, a document, a calendar entry, a document, a news feed, a biometric key, an image, a news feed, etc. A micro-community engine identifies users who are associated explicitly with the object reference as well as people who would be interested in the object implicitly and associates them with a micro-community. The micro-community engine provides an intuitive and flexible means for communication between members of the micro-community.

    摘要翻译: 用于将用户与微社区相关联的与对象引用相关的系统和方法。 对象引用是物理或概念上可以感知的任何东西,例如位置,文档,日历条目,文档,新闻提要,生物识别密钥,图像,新闻提要等。微社区 引擎识别与对象引用明确关联的用户以及隐含对对象感兴趣的人员,并将其与微社区相关联。 微社区引擎为微社区成员之间的沟通提供了直观和灵活的方式。

    METHODS OF ESTABLISHING A COMMUNICATIONS LINK USING PERCEPTUAL SENSING OF A USER'S PRESENCE
    2.
    发明申请
    METHODS OF ESTABLISHING A COMMUNICATIONS LINK USING PERCEPTUAL SENSING OF A USER'S PRESENCE 审中-公开
    使用用户存在的感知建立通信链路的方法

    公开(公告)号:US20070229652A1

    公开(公告)日:2007-10-04

    申请号:US11755734

    申请日:2007-05-30

    IPC分类号: H04N7/14

    CPC分类号: H04N21/44218 H04N7/147

    摘要: A method of establishing a communications link uses automatic sensing of a computer user's presence and activity state to record user attributes in a form accessible to other computers in a communications network. Such automatic sensing may include keyboard/mouse monitors, cameras with associated image processing algorithms, speech detectors, RF radiation detectors, and infrared sensors. Preferably, the attribute recording is done in a server process which can be accessed by other computer programs. A first application of this method is to inform persons at remote locations whether the party to be called is available to receive a call. A second application of the method is to use a Connection Agent to determine whether all desired participants for a conference, or at least a quorum of them, are present and available, so that the conference can be started. A third application of the method is to allow a called party to adjust the kind of notification, if any, he or she receives of an incoming call, depending upon what activity is currently engaging the called party.

    摘要翻译: 建立通信链路的方法使用计算机用户的存在和活动状态的自动感测来以通信网络中的其他计算机可访问的形式记录用户属性。 这种自动感测可以包括键盘/鼠标监视器,具有相关联的图像处理算法的摄像机,语音检测器,RF辐射检测器和红外传感器。 优选地,属性记录在可由其他计算机程序访问的服务器进程中完成。 该方法的第一个应用是通知远程位置的人员是否可以接收呼叫的被叫方。 该方法的第二个应用是使用连接代理来确定是否存在会议的所有期望的参与者,或者至少其中的法定人数,并且可用,以便可以开始会议。 该方法的第三个应用是允许被叫方根据当前正在与被叫方接合的活动来调整他或她接收到来电的通知类型(如果有的话)。

    Modeling scenes in videos using spectral similarity
    4.
    发明申请
    Modeling scenes in videos using spectral similarity 失效
    使用光谱相似性建模视频中的场景

    公开(公告)号:US20060147085A1

    公开(公告)日:2006-07-06

    申请号:US11029787

    申请日:2005-01-05

    IPC分类号: G06K9/00 G06K9/46

    摘要: A computer implemented method models a scene in a video acquired by a camera. For each pixel in each frame of the video, a time series of intensities of the pixel is acquired. A harmonic series is extracted from samples of each time series using a sliding window. Distances between the harmonic series are measured. The distances are an estimate of spectral components in an autocorrelation function of underlying dynamic processes in the scene.

    摘要翻译: 计算机实现的方法对由相机获取的视频中的场景进行建模。 对于视频的每个帧中的每个像素,获取像素的时间序列的强度。 使用滑动窗从每个时间序列的样本中提取谐波序列。 测量谐波系列之间的距离。 距离是场景中基础动态过程的自相关函数中的频谱分量的估计。

    Determining temporal patterns in sensed data sequences by hierarchical decomposition of hidden Markov models
    5.
    发明申请
    Determining temporal patterns in sensed data sequences by hierarchical decomposition of hidden Markov models 失效
    通过隐马尔可夫模型的分层分解确定感测数据序列中的时间模式

    公开(公告)号:US20050256817A1

    公开(公告)日:2005-11-17

    申请号:US10843994

    申请日:2004-05-12

    CPC分类号: G06N99/005 G06K9/6297

    摘要: A method determines temporal patterns in data sequences. A hierarchical tree of nodes is constructed. Each node in the tree is associated with a composite hidden Markov model, in which the composite hidden Markov model has one independent path for each child node of a parent node of the hierarchical tree. The composite hidden Markov models are trained using training data sequences. The composite hidden Markov models associated with the nodes of the hierarchical tree are decomposed into a single final composite Markov model. The single final composite hidden Markov model can then be employed for determining temporal patterns in unknown data sequences.

    摘要翻译: 一种方法确定数据序列中的时间模式。 构建节点的分层树。 树中的每个节点与复合隐马尔可夫模型相关联,其中复合隐马尔可夫模型对于分层树的父节点的每个子节点具有一个独立的路径。 使用训练数据序列训练复合隐马尔可夫模型。 与分层树的节点相关联的复合隐马尔可夫模型被分解为单个最终的复合马尔可夫模型。 然后可以采用单个最终复合隐马尔可夫模型来确定未知数据序列中的时间模式。

    Hierarchical processing in scalable and portable sensor networks for activity recognition
    6.
    发明申请
    Hierarchical processing in scalable and portable sensor networks for activity recognition 有权
    用于活动识别的可扩展和便携式传感器网络中的分层处理

    公开(公告)号:US20070179761A1

    公开(公告)日:2007-08-02

    申请号:US11341649

    申请日:2006-01-27

    IPC分类号: G06F17/10

    CPC分类号: G06K9/00771

    摘要: Binary motion events are detected by individual motion sensors placed in a physical environment. The motions events are transmitted to a cluster leader, each motion detector being a cluster leader of immediately spatially adjacent motion sensors. Movements of objects are detected by the cluster leaders according to the motion events. The movements are transmitted to supercluster leaders, each motion detector being a supercluster leader of immediately spatially adjacent motion clusters of sensors. Activities of the objects are detected by the supercluster leaders, and actions of the objects are detected according to the activities.

    摘要翻译: 通过放置在物理环境中的各个运动传感器检测二进制运动事件。 运动事件被发送到集群领导者,每个运动检测器是立即空间相邻的运动传感器的簇​​头。 根据运动事件,群组领导检测物体的移动。 运动被传送到超群集领导,每个运动检测器是立体空间相邻的运动传感器簇的超群集领导。 物体的活动由超级群星领导检测,物体的动作根据活动进行检测。

    Composite surveillance camera system
    7.
    发明申请
    Composite surveillance camera system 失效
    复合监控摄像系统

    公开(公告)号:US20060284971A1

    公开(公告)日:2006-12-21

    申请号:US11153205

    申请日:2005-06-15

    IPC分类号: H04N7/00

    CPC分类号: H04N5/232 H04N5/2258

    摘要: A method and apparatus acquires images of a scene with an omni-directional imager and a pan-tilt-zoom imager. A relationship between pixels in the input image and locations in the scene is expressed in terms of polar coordinates. An event is detected in the input images and the omni-directional pan-tilt-zoom camera is directed at the event in the scene using the relationship expressed in the polar coordinates.

    摘要翻译: 一种方法和装置利用全向成像器和平移 - 俯仰 - 变焦成像器来获取场景的图像。 输入图像中的像素与场景中的位置之间的关系用极坐标表示。 在输入图像中检测到事件,并且使用极坐标中表达的关系,全景俯仰 - 变焦相机针对场景中的事件。

    Method for processing queries for surveillance tasks
    8.
    发明申请
    Method for processing queries for surveillance tasks 审中-公开
    处理查询任务的方法

    公开(公告)号:US20070257986A1

    公开(公告)日:2007-11-08

    申请号:US11429024

    申请日:2006-05-05

    IPC分类号: H04N7/18

    摘要: A method for querying a surveillance database stores videos and events acquired by cameras and detectors in an environment. Each event includes a time at which the event was detected. The videos are indexed according to the events. A query specifies a spatial and temporal context. The database is searched for events that match the spatial and temporal context of the query, and only segment of the videos that correlate with the matching events are displayed.

    摘要翻译: 用于查询监视数据库的方法存储在环境中由摄像机和检测器获取的视频和事件。 每个事件包括检测到事件的时间。 这些视频根据事件进行索引。 查询指定空间和时间上下文。 搜索与查询的空间和时间上下文匹配的事件的数据库,并且仅显示与匹配事件相关的视频的段。

    Traffic and geometry modeling with sensor networks

    公开(公告)号:US20050080601A1

    公开(公告)日:2005-04-14

    申请号:US10684116

    申请日:2003-10-10

    申请人: Christopher Wren

    发明人: Christopher Wren

    CPC分类号: G05B15/02

    摘要: A method models movement of users in an environment including sensors connected in a network. Events due to movement of the users are detected at the sensors and each event is labeled according to a particular sensor and time of the event. The events for each sensor are summed into a corresponding histogram time interval bin. A plurality of co-occurrence matrices are generated from the histograms according to C i , j , δ = ∑ t = 0 T ⁢   ⁢ H i , t ⁢ H j , t + δ , where i and j represent each possible pair of sensors, δ represent time-off-sets, T is a total time for the detecting, t represents a particular time, and H represents the histogram time interval bins. The co-occurrence matrices can be used to determine a geometry of the network, and for predicting future activities signaled by terminating events.