In compositing applications, objects depicted in images frequently have to be separated from their background, so that they can be placed in a new environment. Alpha mattes are important tools aiding the selection of objects, but cannot normally be created in a fully automatic way. We present an algorithm that requires as input two images - one where the object is in focus, and one where the background is in focus - and then automatically produces an alpha matte indicating which pixels belong to the object. This algorithm is inspired by human visual processing and involves nonlinear response compression, center-surround mechanisms as well as a filling-in stage. The output can then be refined with standard computer vision techniques. Copyrig...
Abstract. We present a multi-view alpha matting method that requires no user input and is able to de...
Over the last few years, deep learning based approaches have achieved outstanding improvements in na...
In this paper we present a novel approach to estimate the alpha mattes of a foreground object captur...
In compositing applications, objects depicted in images frequently have to be separated from their b...
Foreground extraction technology plays an important role in image and video processing tasks. It has...
Defocus matting is a fully automatic and passive method for pulling mattes from video captured with ...
With the development of digital multimedia technologies, image matting has gained increasing interes...
In Mixed Reality scenarios, background replacement is a common way to immerse a user in a synthetic ...
The automatic detection of regions of interest in a video is fundamental for a fast generation of ma...
Image/Video Matting aims at solving the problem of accurate foreground estimation from a given backg...
Image/Video Matting aims at solving the problem of accurate foreground estimation from a given backg...
This paper addresses the problem of extracting an alpha matte from a sin-gle photograph given a user...
Digital matting consists in extracting a foreground element from a background image. Besides the ima...
Image matting is the process to extract an accurate foreground from a given image. The estimated for...
Natural image matting is an important problem in computer vision and graphics. It is an ill-posed pr...
Abstract. We present a multi-view alpha matting method that requires no user input and is able to de...
Over the last few years, deep learning based approaches have achieved outstanding improvements in na...
In this paper we present a novel approach to estimate the alpha mattes of a foreground object captur...
In compositing applications, objects depicted in images frequently have to be separated from their b...
Foreground extraction technology plays an important role in image and video processing tasks. It has...
Defocus matting is a fully automatic and passive method for pulling mattes from video captured with ...
With the development of digital multimedia technologies, image matting has gained increasing interes...
In Mixed Reality scenarios, background replacement is a common way to immerse a user in a synthetic ...
The automatic detection of regions of interest in a video is fundamental for a fast generation of ma...
Image/Video Matting aims at solving the problem of accurate foreground estimation from a given backg...
Image/Video Matting aims at solving the problem of accurate foreground estimation from a given backg...
This paper addresses the problem of extracting an alpha matte from a sin-gle photograph given a user...
Digital matting consists in extracting a foreground element from a background image. Besides the ima...
Image matting is the process to extract an accurate foreground from a given image. The estimated for...
Natural image matting is an important problem in computer vision and graphics. It is an ill-posed pr...
Abstract. We present a multi-view alpha matting method that requires no user input and is able to de...
Over the last few years, deep learning based approaches have achieved outstanding improvements in na...
In this paper we present a novel approach to estimate the alpha mattes of a foreground object captur...