Foreground target detection algorithm (FTDA) is a fundamental preprocessing step in computer vision and video processing. A universal background subtraction algorithm for video sequences (ViBe) is a fast, simple, efficient and with optimal sample attenuation FTDA based on background modeling. However, the traditional ViBe has three limitations: (1) the noise problem under dynamic background; (2) the ghost problem; and (3) the target adhesion problem. In order to solve the three problems above, ant colony clustering is introduced and Ant_ViBe is proposed in this paper to improve the background modeling mechanism of the traditional ViBe, from the aspects of initial sample modeling, pheromone and ant colony update mechanism, and foreground segmentation criterion. Experimental results show that the Ant_ViBe greatly improved the noise resistance under dynamic background, eased the ghost and targets adhesion problem, and surpassed the typical algorithms and their fusion algorithms in most evaluation indexes.

中文翻译：

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Ant_ViBe：动态背景下基于蚁群聚类的改进ViBe算法

前景目标检测算法（FTDA）是计算机视觉和视频处理中的基本预处理步骤。通用的视频序列背景减除算法（ViBe）是一种快速，简单，高效且具有基于背景建模的最佳样本衰减FTDA的算法。但是，传统的ViBe具有三个局限性：（1）动态背景下的噪声问题；（2）幻影问题；（3）目标附着力问题。为了解决上述三个问题，从初始样本建模，信息素和蚁群更新机制以及前景分割等方面介绍了蚁群聚类，并提出了Ant_ViBe来改进传统ViBe的背景建模机制。标准。