Dynamic scenes reconstruction based on foreground and background splitting

WCSP(2013)

引用 2|浏览15
暂无评分
摘要
In recent years, several approaches have been proposed to reconstruct static scenes. However, there exists rarely method for dynamic scenes. In this paper, we propose an approach to reconstruct dynamic scenes using only a moving depth sensor. The main idea is to reconstruct the moving foreground objects and static background scenes respectively. An iterative closest point (ICP) algorithm is used for obtaining the current camera pose. The foreground and background splitting is achieved by processing failed tracking points. We introduce an efficient filter and morphological operations to handle these points. Finally, foreground and background models are reconstructed separately using the split depth data and the calculated camera pose. Experimental results demonstrate that our method has fast and robust performance in reconstructing complex dynamic scenes.
更多
查看译文
关键词
camera pose,depth sensors,background models,reconstruction,failed tracking points,complex dynamic scene reconstruction,morphlogical operations,efficient filter operations,iterative closest point algorithm,icp,static scenes,dynamic scenes,image reconstruction,augmented reality,foreground splitting,cameras,foreground models,background splitting,morphological operations,filtering theory,iterative methods
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要