Multi-View Depth-Based Trimap Generation for Automatic Natural Image Matting

• Main Authors: Huang, Chun Yin, 黃俊穎
• Other Authors: Huang, Chao Tsung
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/hjx7m8

碩士 === 國立清華大學 === 電機工程學系 === 105 === Image matting is the problem of extracting foreground components from an image. Among all matting algorithms, additional user input is required during matting process since it is inherently an under-constrained problem. A trimap is a general and popular user input that segments the image into three parts: foreground, background, and unknown region. The accuracy of a trimap directly affects the computation time and matting quality for alpha matting algorithms. However, a good trimap is usually drawn manually in literature, which is a tedious and time-consuming process. We aim to design an algorithm to generate a trimap that requires only simple user input but delivers good results for the followed alpha matting algorithm. With the help of light field capturing, we use multi-view and depth information to design an automatic trimap generation. Based on them, we segment the original image and generate the corresponding initial trimap. We also design a background sampling-based algorithm which is used to refine the initial trimap to generate the final trimap. We will show that our trimap can increase not only estimation accuracy but also computation efficiency for image matting. Both subjective and objective experiments will be given to demonstrate these advantages. Take closed-form matting for example, we will prove the number of pixels in unknown region is proportional to computation time, so the more foreground and background pixels we specify in our trimap, the less computation time needed in matting process.