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    • 9. 发明公开
    • OBJECT RECOGNITION DEVICE
    • 对象识别装置
    • EP2722815A1
    • 2014-04-23
    • EP12800268.0
    • 2012-06-14
    • Toyota Jidosha Kabushiki KaishaEidgenossische Technische Hochschule Zurich
    • RAZAVI, NimaGALL, JürgenVAN GOOL, LucFUNAYAMA, Ryuji
    • G06T7/00
    • G06K9/6267G06K9/00791G06K9/00805G06K9/4633G06K9/6219G06K9/6282G06K2209/27
    • A learning unit 4 generates a function table indicating the relationship between the class number and position information of an object and the probability of appearance of the object for each small area image pattern of a code book, calculates a sharing matrix indicating the commonality of a feature amount between the classes, makes a tree diagram in which the classes with a similar feature amount are clustered, and calculates the weight of each node in the tree diagram for each small area image pattern. The recognition processing unit 7 compares image data captured by a camera 2 with the code book, selects the closest small area image pattern among a plurality of small area image patterns, extracts the class related to the node with the smallest weight among the nodes with a weight equal to or greater than a threshold value for the selected small area image pattern, and votes the position information of the small area image pattern for the class, thereby recognizing the object.
    • 学习单元4针对代码簿的每个小区域图像图案生成指示对象的类别编号和位置信息与对象的出现概率之间的关系的函数表,计算指示特征的共性的共享矩阵 量之间的量,制作树图,其中具有相似特征量的类被聚类,并计算每个小区域图像图案的树状图中每个节点的权重。 识别处理单元7将由照相机2捕获的图像数据与码本进行比较,从多个小区域图像图案中选择最近的小区域图像图案,并将与节点中具有最小权重的节点有关的类别与 对于所选择的小区域图像图案,选择等于或大于阈值的权重,并且针对该类别投票小区域图像图案的位置信息,由此识别该目标。