Abstract: Vibe algorithm runs very quickly and can reduce the impact of shadow and the shaking of a camera effectively, and has a good performance for foreground detection. But for those dynamic background outdoor videos, it’s inevitable to avoid the background disturbance, and the algorithm can’t achieve precise foreground detection. To solve the problem, a novel strategy combined Vibe algorithm with color information is proposed. Pixels are converted from RGB space to HSV space to compute pixel color distortion. And the amount of calculation is obviously reduced due to the construction of Dual model. Experiments show that the algorithm can obtain more accurate detection property for moving objects, and has showed well robustness against disturbance.

Key words: object detection, Vibe algorithm, background modeling, YUV color space

摘要： Vibe算法运行速度较快，并能快速有效地抑制阴影、照相机晃动对前景检测造成的影响，具有较好的前景检测性能。但对于存在动态背景的户外视频，不可避免地存在背景干扰及噪声的影响，使得Vibe算法不能准确地检测出运动目标。针对此缺陷，提出颜色特征信息与Vibe相结合的改进算法，将像素点从RGB空间转换到HSV颜色空间进行颜色失真度比较，通过双模型的建立，有效减少了计算量。系列实验表明该方法能够取得更加准确的前景分割特性，对噪声干扰表现出良好的鲁棒性。

关键词: 目标检测, Vibe算法, 背景建模, YUV颜色空间