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    • 3. 发明申请
    • ABNORMAL BEHAVIOUR DETECTION
    • 异常行为检测
    • US20150071492A1
    • 2015-03-12
    • US14397340
    • 2013-04-26
    • BAE SYSTEMS plc
    • Jordi McGregor BarrYoann Paul Georges ThueuxMark Robert Goodall
    • G08B13/196G06N99/00G06N7/00G06T7/20
    • G08B13/19608G06N7/005G06N20/00G06T7/20G06T2207/20076G06T2207/20081G06T2207/30196G06T2207/30232G08B13/19613
    • Methods and apparatus for determining whether a provided object track (24) is abnormal, an object track (24) being a set of values of a physical property of an object (2) measured over a period of time, the method comprising: providing a model comprising one or more functions (26), each function (26) being representative of an object track (24) that is defined to be normal; assigning the provided object track (24) to a function (26); and comparing the provided object track (24) to the assigned function (26) to determine whether that object track (24) is abnormal. Providing the model comprises: for each of a plurality of objects (2), determining an object track (24), wherein the determined object tracks (24) are defined as normal object tracks (24); and using the determined tracks (24), performing a Gaussian Processes based Variational Bayes Expectation Maximisation process to learn the one or more functions (26).
    • 用于确定所提供的物体轨道(24)是否异常的方法和装置,所述物体轨道(24)是在一段时间内测量的物体(2)的物理属性的值的集合,所述方法包括:提供 包括一个或多个功能(26)的模型,每个功能(26)表示被定义为正常的物体轨道(24); 将所提供的物体轨道(24)分配给功能(26); 以及将所提供的物体轨道(24)与所分配的功能(26)进行比较,以确定所述物体轨迹(24)是否异常。 提供模型包括:对于多个对象(2)中的每一个,确定对象轨道(24),其中所确定的对象轨道(24)被定义为普通对象轨道(24); 以及使用确定的轨道(24),执行基于高斯过程的变异贝叶斯期望最大化过程来学习一个或多个函数(26)。
    • 4. 发明授权
    • Optical inertial measurement apparatus and method
    • US10401175B2
    • 2019-09-03
    • US15520580
    • 2015-01-30
    • BAE SYSTEMS plc
    • James Duncan RevellMark Robert GoodallGary Martin Cross
    • G06K9/00G01C21/16G06T7/70
    • An optical inertial measurement method for determining a 6DOF pose in respect of a moving platform, the method comprising providing, in respect of said moving platform, a camera unit (10) comprised of at least three monocular cameras (14, 16, 18) connected rigidly together and configured such that their fields of view do not overlap and cover motion of said platform in each of three principal, substantially orthogonal axes; receiving video outputs from each of said cameras; determining individual point correspondences from said video outputs, and estimating therefrom, for each camera, a transform that includes translation values representative of direction of translation in the x and y axes, rotation about the optical axis and a scale factor, each transform being expressed with respect to a local 3D coordinate system associated with a respective camera; and mapping said translation values in the x and y axes to a global 3D coordinate system, having its origin defined by a point between said cameras, and multiplying said translation values by a respective scale factor so as to determine a 6DOF pose in respect of said camera unit.An optical inertial measurement system is also disclosed.