Optimized dynamic background subtraction technique for moving object detection and tracking
Rahul Dutt Sharma, Shubh Lakshmi Agrwal, Sandeep K. Gupta, Anil Prajapati
- 发表年份
- 2017
- 引用次数
- 17
摘要
Moving Object detection and tracking in a video have applications in video-surveillance and robotics, human-computer interaction. Three frame differencing is better than two frames difference technique due to fewer problems of holes. Dynamic background detection technique is much better than static background technique for video with background change. So in this paper, background is updated with averaging of frame t-1, frame t+1 and previous updated background. This updated background is subtracted from frame t for foreground detection and merged with three frame subtraction. So there is scope of work such that holes problem should be reduced more and object should be detected better in dynamic changes in background. In this work, the proposed technique is able to reduce the holes problem in dynamic background updating video. This technique is extract foreground better than existing static and dynamic background.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002