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    • 2. 发明申请
    • TRACKING ON-ROAD VEHICLES WITH SENSORS OF DIFFERENT MODALITIES
    • 跟踪具有不同模式传感器的道路车辆
    • US20140032012A1
    • 2014-01-30
    • US13556802
    • 2012-07-24
    • Avdhut S. JOSHIMichael R. JamesMichael E. Samples
    • Avdhut S. JOSHIMichael R. JamesMichael E. Samples
    • G06F17/00
    • G01S13/931G01S7/2955G01S13/865G05D1/024G05D1/0257G05D1/0274G05D2201/0213G08G1/166
    • A vehicle system includes a first sensor and a second sensor, each having, respectively, different first and second modalities. A controller includes a processor configured to: receive a first sensor input from the first sensor and a second sensor input from the second sensor; detect, synchronously, first and second observations from, respectively, the first and second sensor inputs; project the detected first and second observations onto a graph network; associate the first and second observations with a target on the graph network, the target having a trajectory on the graph network; select either the first or the second observation as a best observation based on characteristics of the first and second sensors; and estimate a current position of the target by performing a prediction based on the best observation and a current timestamp.
    • 车辆系统包括第一传感器和第二传感器,每个具有不同的第一和第二模态。 控制器包括处理器,其被配置为:从第一传感器接收第一传感器输入和从第二传感器输入的第二传感器; 分别从第一和第二传感器输入端检测,同步,第一和第二观测值; 将检测到的第一和第二观测项目投影到图形网络上; 将第一和第二观察结果与图形网络上的目标相关联,目标在图形网络上具有轨迹; 基于第一和第二传感器的特性,选择第一或第二观察作为最佳观察; 并且通过基于最佳观察和当前时间戳执行预测来估计目标的当前位置。
    • 8. 发明授权
    • System and method for object recognition based on three-dimensional adaptive feature detectors
    • 基于三维自适应特征检测器的物体识别系统和方法
    • US08687898B2
    • 2014-04-01
    • US12697808
    • 2010-02-01
    • Danil V. ProkhorovMichael R. James
    • Danil V. ProkhorovMichael R. James
    • G06K9/62
    • G06K9/00
    • Method and system for imaging an object in three-dimensions, binning data of the imaged object into three dimensional bins, determining a density value p of the data in each bin, and creating receptive fields of three dimensional feature maps, including processing elements O, each processing element O of a same feature map having a same adjustable parameter, weight Wc1. The density values p are processed with the processing elements O to determine an output value o for at least each three dimensional location of the imaging of the object having a density value p above a predetermined threshold value. An object is classified by processing the output values o with a committee of classifiers, and the classification of the object is communicated.
    • 用于将成像对象的三维数据成像成三维仓的方法和系统,确定每个仓中的数据的密度值p,以及创建三维特征图的接收场,包括处理元素O, 相同特征图的每个处理元件O具有相同的可调参数,权重Wc1。 密度值p用处理元件O处理,以确定具有高于预定阈值的浓度值p的物体的成像的至少每个三维位置的输出值o。 通过用分类器委员处理输出值o来分类对象,并传达对象的分类。