Image and Video Matting

A Survey
1. Auflage 2008
ISBN: 978-1-60198-134-9
Verlag: Now Publishers

Buch, Englisch, Band 9, 88 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Foundations and Trends® in Computer Graphics and Vision

If you've ever wanted to add that missing member of your family to a group photograph, you can now, given newly developed technology. Simply find a picture of the missing person, determine a "matte" that will lift them out and leave the background behind, and use the matte to insert them in the original image. Matting refers to the problem of accurate foreground estimation in images and video. The matte defines which pixels are foreground, which are background, and for pixels along the boundary or in semi-transparent regions such as hair, the matte defines the mixture of foreground and background at each pixel. Matting is one of the key techniques in many image editing and film production applications, thus has been extensively studied in the research 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 professionals as well as consumers. Consequently, various matting techniques and systems have been proposed to try to efficiently extract high quality mattes from both still images and video sequences. Image and Video Matting: A Survey provides a comprehensive review of existing image and video matting algorithms and systems, with an emphasis on the advanced techniques that have been recently proposed. Various methods are described and contrasted and finally tested against a uniform set of examples. Image and Video Matting: A Survey is most appropriate for a graduate level course in computational photography, or for any student or serious practitioner interested in the inner workings of matting methods.

Autoren/Hrsg.

Wang, Jue

Cohen, Michael F.

Inhaltsverzeichnis

1: Introduction 2: Color Sampling Methods for Matting 3: Defining Affinities for Matting 4: Optimization by Combining Sampling and Affinities 5: Performance Evaluation 6: Extension to Video 7: Matting with Extra Information 8: Conclusion. Acknowledgements. References.