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A Weight Joint-Based Clustering (WJC) Method for Secure Monitoring System

机译:一种用于安全监控系统的重量联合聚类(WJC)方法

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Currently, 3D depth sensors are used in monitoring systems to give accurate results in identifying objects. The existing monitoring systems which use 3D sensors are effective in recognizing object gestures, but do not consider an object’s change in location. This paper proposes a new system that uses a 3D camera sensor and weight joint-based in clustering method to identify objects’ change in location and to recognize object activities, using a 3D camera to capture the depth value of an object in order to measure its location with the aid of position data of the object’s joints. Because the system uses depth value to identify the object’s location, it does not require any extra processes for improving the accuracy of clustering where the object is available. The system provides 100% accuracy when recognizing objects’ activities has low processing time and is cost effective.
机译:目前,3D深度传感器用于监控系统,以便在识别对象方面提供准确的结果。使用3D传感器的现有监视系统在识别对象手势方面有效,但不考虑对象的位置变化。本文提出了一种新的系统,它使用3D摄像机传感器和基于群集方法的重量联合,以识别对象的变化,并使用3D相机捕获对象的深度值以捕获对象的深度值以便测量其位置借助物体关节的位置数据。由于系统使用深度值来标识对象的位置,因此它不需要任何额外的进程来提高对象可用的群集的准确性。当识别物体的活动具有低处理时间并且具有成本效益时,该系统提供了100%的准确性。

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