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POSE AND SUB-POSE CLUSTERING-BASED IDENTIFICATION OF INDIVIDUALS

机译:基于姿势和子位置聚类的个人标识

摘要

The subject matter discloses systems and methods for identification of individuals. The method includes obtaining static and dynamic feature vectors for skeleton data frames of each individual performing a step activity with an arbitrary pattern and in a random path; creating, for the each individual, a first predefined number of clusters of dynamic feature vectors for the frames; creating, for the each individual, a second predefined number of sub-clusters within the each of the clusters of the dynamic feature vectors for the frames associated with the each of the clusters; and determining, for the each individual, a gait-pose feature data set based on computation of a center of the dynamic feature vectors for the frames associated with the each of the sub-clusters, and a mean of the static feature vectors for the frames associated with the each of the clusters, for identifying the individuals.
机译:该主题公开了用于识别个人的系统和方法。该方法包括获得用于以任意模式和在随机路径中执行阶梯活动的每个个体的骨架数据帧的静态和动态特征矢量;以及为每个个体为帧创建第一预定义数量的动态特征矢量簇;为每个个体在动态特征矢量的每个聚类中为与每个聚类相关联的帧创建第二预定数量的子聚类;根据每个与子集群相关联的帧的动态特征向量的中心以及这些帧的静态特征向量的平均值,为每个个体确定步态姿势特征数据集与每个集群相关联,以识别个人。

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