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Application of design of image tracking by combining SURF and TLD and SVM-based posture recognition system in robbery pre-alert system

机译：SURF与TLD相结合的图像跟踪设计与基于SVM的姿态识别系统在抢劫预警系统中的应用

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This paper describes the design of an image tracking system that combines Speeded Up Robust Features (SURF) and Tracking-Learning-Detection (TLD), with a posture recognition system that is based on the Support Vector Machine (SVM), and includes image tracking, foreground detection and posture recognition. Image tracking, which combines the SURF and the TLD algorithms, starts by detecting the postures of a specific person with SURF, before tracking the object using TLD. Foreground detection uses the Codebook background subtraction algorithm to acquire foreground images and mends them by post-processing. Lastly, posture recognition applies SVM to determine human body postures. This article embodies such a system by applying it in a robbery pre-alert system.
机译：本文介绍了结合了加速鲁棒特征（SURF）和跟踪学习检测（TLD）以及基于支持向量机（SVM）的姿势识别系统的图像跟踪系统的设计，其中包括图像跟踪，前景检测和姿势识别。结合了SURF和TLD算法的图像跟踪，首先是使用SURF检测特定人的姿势，然后再使用TLD跟踪对象。前景检测使用Codebook背景扣除算法来获取前景图像并通过后处理对其进行修补。最后，姿势识别将支持向量机用于确定人体姿势。本文通过将其应用于抢劫预警系统来体现这种系统。

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