CAJ | 학술논문

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。
Vibe산법운행속도교쾌，병능쾌속유효지억제음영、조상궤황동대전경검측조성적영향，구유교호적전경검측성능。단대우존재동태배경적호외시빈，불가피면지존재배경간우급조성적영향，사득Vibe산법불능준학지검측출운동목표。침대차결함，제출안색특정신식여Vibe상결합적개진산법，장상소점종RGB공간전환도HSV안색공간진행안색실진도비교，통과쌍모형적건립，유효감소료계산량。계렬실험표명해방법능구취득경가준학적전경분할특성，대조성간우표현출량호적로봉성。
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.