Video matting

• Main Author: Rishi Venkat.
• Other Authors: Deepu Rajan
• Format: Final Year Project
• Language: English
• Published: 2012
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
• Online Access: http://hdl.handle.net/10356/48579
• Institution: Nanyang Technological University

Matting refers to the problem of accurate foreground estimation in images and videos. 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 advancements in digital cameras, the use of matting techniques for editing or to create interesting and novel composites has gained increasing interest. Consequently, various matting techniques and systems have been proposed to try to efficiently extract high quality mattes from both still images and video sequences. A matte refers to an image in which the foreground has been estimated and isolated from the background in the image. In video matting, the process of foreground isolation is carried out for a video sequence. The objective is to make a clear distinction between the foreground and the background and allow the same to be propagated throughout the video sequence. Many techniques have been derived in attempts to provide a solution. One such technique that aims to simplify the model shall be discussed and analysed here. This project implements a method of isolating the foreground from the background for a given sequence of video frames. The method has been implemented in MATLAB and it aims to minimize user interaction. After the matte has been extracted, the foreground can be composited with other backgrounds to yield new videos. This finds enormous applications in video clip editing, movies and commercials. However, there are a few areas where the existing algorithm can be improved on so that it can become a highly robust method of background generation. This report describes the testing and implementation plans and results of the experiment as well as an analysis of the results. Finally, it also attempts to provide a conclusion and a recommendation for the improvement of the algorithm.