基于Grabcut和改进ViBe相结合的背景减影算法

Shuihan Jiang, Yunqi Gao, Changying Wang, Junting Qi, Li Cheng, Xiaojuan Zhang
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引用次数: 1

摘要

背景减法算法是视频处理的关键。例如目标跟踪、手势识别和步态识别。ViBe因其易于实现和效率高而得到了广泛的应用。然而,当运动目标的速度发生变化时,该算法会产生鬼影成像。另一方面,ViBe对环境变化的适应能力受到挑战,容易将阴影误认为前景目标。此外,它也不能很好地处理由相机抖动引起的干扰。针对ViBe的不足,我们提出了一种新的算法Gc_IViBe,该算法综合了Grabcut和Improved ViBe (IViBe)的优点。基于IViBe消除鬼影成像的能力,该算法利用HSV空间中的掩模去除背景阴影。结合IViBe和Grabcut,进一步改进了算法在处理空腔问题和相机抖动方面的性能。实验结果表明,Gc_IViBe在像素级测量精度、结构测量S-measure和E-measure方面都优于ViBe。本文还对评价方法进行了探讨。在某些情况下,精度和S-measure的评价结果与真实情况存在明显差异。而E-measure的一致性表现相对较好,能够准确地评估本文提出的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Background Subtraction Algorithm Based on Combination of Grabcut and Improved ViBe
Background subtraction algorithm is essential for video processing. such as target tracing, gesture recognition and gait recognition. ViBe has been widely used because of easy implementation and high efficiency. However, the algorithm would produce a ghost imaging when the speed of the moving target changes. On the other hand, ViBe is challenged to adapt to the change of environment and by misjudge the shadow as the foreground target. Moreover, it is also inability to handle well the interference caused by camera jitter. Aiming to the deficiencies of ViBe, we propose a new algorithm Gc_IViBe, which takes advantages from both Grabcut and Improved ViBe (IViBe). Based on the ability of IViBe to eliminate ghost imaging, the proposed algorithm utilizes mask in HSV space to remove background shadows. A further improvement of the algorithm in handling cavity problem and camera jitter is achieved by combinating IViBe and Grabcut. The experimental results show that Gc_IViBe performs better than ViBe in Pixel-level measure Precision, Structural measures S-measure and E-measure. This paper also discusses the evaluation methods. The evaluation results of Precision and S-measure in some cases are apparently different from the truth. while E-measure performs relatively better consistent, which capable to accurately evaluate the problems raised in this article.
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