动态场景的背景重建

M. Xiao, Chongzhao Han, Xin Kang
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引用次数: 28

摘要

基于背景不是序列中短时间出现的部分的假设,提出了一种基于在线聚类的背景重构算法。首先,基于在线聚类对像素强度进行分类;其次,计算聚类中心和每个聚类的出现概率;最后,选取出现概率大于阈值的单或多强度簇作为背景像素强度值。仿真结果表明,该算法能够表示背景包含双模型或多模型分布的情况,能够正确地进行运动分割。该算法具有计算量小、内存小的特点,能够满足实时性的要求
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Background Reconstruction for Dynamic Scenes
Based on assumption that background would not be the parts which appear in the sequence for a short time, a background reconstruction algorithm based on online clustering was proposed in this paper. Firstly, pixels intensities are classified based on online clustering. Secondly, cluster centers and appearance probabilities of each cluster are calculated. Finally, a single or multi intensities clusters with the appearance probability greater than threshold are selected as the background pixel intensity value. Simulation results show that the algorithm can represent situation where the background contains bi-model or multi-model distribution, and motion segmentation can be performed correctly. The algorithm with inexpensive computation and low memory can accommodate the real-time need
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