Automatic Trimap Generation for Image Matting
This addresses the challenge of reducing human effort in image matting for computational photography applications, though it is incremental as it builds on existing learning-based matting methods.
The paper tackles the problem of automating image matting by proposing a method to automatically generate trimaps from input images, eliminating the need for human intervention. Experimental results show that the automatically generated trimaps produce accurate matte estimation, validated by comparisons with manually created trimaps.
Image matting is a longstanding problem in computational photography. Although, it has been studied for more than two decades, yet there is a challenge of developing an automatic matting algorithm which does not require any human efforts. Most of the state-of-the-art matting algorithms require human intervention in the form of trimap or scribbles to generate the alpha matte form the input image. In this paper, we present a simple and efficient approach to automatically generate the trimap from the input image and make the whole matting process free from human-in-the-loop. We use learning based matting method to generate the matte from the automatically generated trimap. Experimental results demonstrate that our method produces good quality trimap which results into accurate matte estimation. We validate our results by replacing the automatically generated trimap by manually created trimap while using the same image matting algorithm.