Earticle

초록

영어

As the Microsoft’s Kinect sensor can generate a real-time dense depth map with relatively commercial available, it is widely used in depth map capturing. However, there are some artifacts like holes, instability of the raw input data, which seriously affect the application. To solve this problem, in this paper, we propose a novel depth map refinement method based on by GMM and CS theory which enable the kinect sensor generate a dense depth map, the background large holes are filled without blurring, and the edges of the objects are sharpened, median filter is used to remove noise. Experiments on captured indoor data demonstrate the effectiveness of the method especially in the edge area and occlusion area that our method can obtain better results.

목차

Abstract
 1. Introduction
 2. Optimization of depth map based on GMM
 3. Overview of Compressive Sensing
 4. Depth Map Reconstruction and View Rendering
 5. Results
 6. Conclusion
 ACKNOWLEDGEMENTS
 References

키워드

저자

• Qian Zhang [ College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ]
• ShaoMin Li [ College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ]
• Wenfeng Guo [ College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ]
• Pei Wang [ College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ]
• Jifeng Huang [ College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605