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    • 4. 发明公开
    • VIDEO-ASSISTED TARGET LOCATION
    • VIDEOUNTERSTÜTZTEZIELSUCHE
    • EP2901236A1
    • 2015-08-05
    • EP13737491.4
    • 2013-06-27
    • Raytheon Company
    • KARLOV, Valeri I.DURST, Adam C.BARRY, Patrick E.
    • G06D1/02G06T7/00G06T7/20
    • G06T7/208G06T7/277G06T7/579G06T2207/10016G06T2207/10032G06T2207/30212G06T2207/30244
    • A method for locating features in a field of view of an imaging sensor that includes receiving image data from the field of view of an imaging sensor, wherein the image data includes a plurality of image frames. The method also includes receiving three-dimensional position measurements, in an absolute coordinate system, for the imaging sensor at the point in time each image frame is acquired and identifying one or more features in each of the image frames. The method also includes determining position and velocity of the one or more features in the image frames based on changes to the one or more features between the image frames and determining three-dimensional positions of the one or more features in the image frames based on the received three-dimensional position measurements for the imaging sensor and position and velocity of the one or more features in the image frames.
    • 一种用于定位成像传感器的视场中的特征的方法,其包括从成像传感器的视场接收图像数据,其中所述图像数据包括多个图像帧。 该方法还包括在绝对坐标系中接收在每个图像帧获取的时间点处的成像传感器的三维位置测量,并且识别每个图像帧中的一个或多个特征。 该方法还包括基于对图像帧之间的一个或多个特征的改变来确定图像帧中的一个或多个特征的位置和速度,并且基于图像帧中的一个或多个特征确定三维位置 接收成像传感器的三维位置测量以及图像帧中的一个或多个特征的位置和速度。
    • 8. 发明申请
    • OBJECT TRACKING DEVICE, OBJECT TRACKING METHOD, AND OBJECT TRACKING PROGRAM
    • 对象跟踪设备,对象跟踪方法和对象跟踪程序
    • US20120093364A1
    • 2012-04-19
    • US13263169
    • 2011-01-13
    • Yuji Sato
    • Yuji Sato
    • G06K9/00
    • G06T7/208G06T7/277G06T2207/10016G06T2207/20076
    • An object tracking apparatus is provided that enables the possibility of erroneous tracking to be further reduced. An object tracking apparatus (300) is an apparatus that tracks the position of an object displayed in video using a particle filter, and has: a feature calculation section (340) that generates a plurality of particles indicating candidates for the position of the object, and calculates a feature of an image of the object and features of images of the particles; a likelihood calculation section (350) that calculates, for each particle, the likelihood of that particle being the position of the object from similarity between a feature of an image of that particle and a feature of an image of the object; a position estimation section (360) that estimates the position of the object based on the calculated particle likelihood; and a likelihood correction section (390) that performs likelihood correction when there are a plurality of objects and a plurality of positions estimated in correspondence to these overlap.
    • 提供了一种能够进一步减少错误跟踪的可能性的对象跟踪装置。 物体跟踪装置(300)是使用粒子滤波器跟踪在视频中显示的对象的位置的装置,具有:特征计算部(340),其生成表示对象的位置的候选的多个粒子, 并计算对象的图像的特征和粒子的图像的特征; 对于每个粒子,对于该粒子的图像的特征与对象的图像的特征之间的相似性,计算该粒子的位置的似然度的似然度计算部(350) 位置估计部(360),其基于所计算的粒子似然率来估计所述对象的位置; 以及当存在多个对象时执行可能性校正的似然性校正部(390),并且与这些对应度对应地估计的多个位置。
    • 10. 发明申请
    • TARGET TRACKING
    • 目标跟踪
    • US20130006577A1
    • 2013-01-03
    • US13635193
    • 2011-03-08
    • George Morgan MathewsDavid Nicholson
    • George Morgan MathewsDavid Nicholson
    • G06F17/18
    • G06T7/208G01S13/726G06T7/277
    • An apparatus and a method are disclosed for tracking a plurality of targets (e.g. land-based vehicles). The method can include: for a first time-step, estimating a state of each respective target; at a second time-step, measuring values for a state of each target; for the second time-step, estimating a state of each target using the estimated target states for the first time-step; updating the estimated target states for the second time-step by performing a Joint Probabilistic Data Association process using the measured values; and performing an identity management process to estimate a probability that a particular state measurement corresponds to a particular.
    • 公开了用于跟踪多个目标(例如陆基车辆)的装置和方法。 该方法可以包括:对于第一时间步长,估计每个相应目标的状态; 在第二时间步长测量每个目标的状态的值; 对于所述第二时间步长,使用所述第一时间步长的估计目标状态来估计每个目标的状态; 通过使用测量值执行联合概率数据关联过程来更新第二时间步长的估计目标状态; 以及执行身份管理过程以估计特定状态测量对应于特定状态测量的概率。