In this paper, we propose an automatic alpha matting method that improves the quality of alpha matte using a depth camera. Depth camera obtains both visual and depth information of moving objects in real time. Our matting method improves existing natural alpha matting methods by adding depth information. Experimental results demonstrate that our matting method generates better results than the ...

Matting refers to the problem of accurate foreground estimation in images and video. It is one of the key techniques in many image editing and film production applications, thus has been extensively studied in the literature. With the recent advances of digital cameras, using matting techniques to create novel composites or facilitate other editing tasks has gained increasing interest from both...

We present an algorithm for extracting high quality temporally coherent alpha mattes of objects from a video. Our approach extends the conventional image matting approach, i.e. closed-form matting, to video by using multi-frame nonlocal matting Laplacian. Our multi-frame nonlocal matting Laplacian is defined over a nonlocal neighborhood in spatial temporal domain, and it solves the alpha mattes...

In this paper, we are concerned with unsupervised natural image matting. Due to the under-constrained nature of the problem, image matting algorithms are usually provided with user interactions, such as scribbles or trimaps. This is a very tedious task and may even become impractical for some applications. For unsupervised matte calculation, we can either adopt a technique that supports an unsu...

In this paper, we formulate the problem of natural image matting as one of solving Poisson equations with the matte gradient field. Our approach, which we call Poisson matting, has the following advantages. First, the matte is directly reconstructed from a continuous matte gradient field by solving Poisson equations using boundary information from a user-supplied trimap. Second, by interactivel...

Video matting attempts to extract foreground images from an image sequence, as well as the alpha-mattes that describe their transparency. This papers presents an automated video matting framework using motion-based segmentation and bayesian matting. We build upon existing techniques for layer segmentation based on optical flow to generate a coarse trimap, by identifying image pixels as belongin...

This paper proposes a novel approach to solve the matting problem on complex images using Markov Random Field(MRF) model. Although many natural image matting methods have been proposed, matting on complex images still remains as a challenge. Our approach, which we call MRF matting, partitions the image manually into three regions: foreground, background, and unknown region. Then, the unknown re...

Extracting foreground objects from an arbitrary natural image or video sequences has become a classical problem in many photo-editing and video compositing applications. This topic has been deeply studied because it's widely used in filming and image rendering industry. With the recent developments in imaging sensors and computing technologies, image matting has become more attractive not only ...

In this paper, we propose a new matting algorithm using local and nonlocal neighbors. We assume that K nearest neighbors satisfy the color line model that RGB distribution of the neighbors is roughly linear and combine this assumption with the local color line model that RGB distribution of local neighbors is roughly linear. Our assumptions are appropriate for various regions such as those that...

Image matting aims at extracting foreground from a given image by means of color and alpha estimation. An automatic matting method based on saliency detection was proposed in this paper, which takes the advantages of saliency detection as prior information instead of user interaction. After getting the saliency map, a cost function was constructed to obtain an alpha matte. Moreover, with the in...