Separating foreground objects from natural images and video plays an important role in image and video editing tasks. Despite extensive study in the last two decades, this problem still remains challenging. In particular, extracting a foreground object in a static image involves determining both full and partial pixel coverage, also known as extracting a matte, which is a severely under-constrained problem. Segmenting spatio-temporal video objects from a video sequence is even harder since extracted foregrounds on adjacent frames must be both spatially and temporally coherent. Previous approaches usually require a large amount of user input and still suffer from inaccurate results and low computational efficiency. This book demonstrates efficient and accurate foreground extraction methods and systems by combining advanced computational algorithms with novel user interfaces. Our systems are capable of extracting high quality foreground objects from images and video with a limited amount of user input such as a few paint strokes of the mouse. We also demonstrate a variety of applications with the extracted foreground objects.
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Separating foreground objects from natural images and video plays an important role in image and video editing tasks. Despite extensive study in the last two decades, this problem still remains challenging. In particular, extracting a foreground object in a static image involves determining both full and partial pixel coverage, also known as extracting a matte, which is a severely under-constrained problem. Segmenting spatio-temporal video objects from a video sequence is even harder since extracted foregrounds on adjacent frames must be both spatially and temporally coherent. Previous approaches usually require a large amount of user input and still suffer from inaccurate results and low computational efficiency. This book demonstrates efficient and accurate foreground extraction methods and systems by combining advanced computational algorithms with novel user interfaces. Our systems are capable of extracting high quality foreground objects from images and video with a limited amount of user input such as a few paint strokes of the mouse. We also demonstrate a variety of applications with the extracted foreground objects.
Dr. Jue Wang received bachelor and master degrees from Tsinghua University, China, and Ph.D. degree in Electrical Engineering from the University of Washington in 2007. He joined Adobe Systems in 2007, and presently is a senior research scientist. His research interests include computational photography and video, image and video processing.
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Taschenbuch. Zustand: Neu. Neuware -Separating foreground objects from natural images and video plays an important role in image and video editing tasks. Despite extensive study in the last two decades, this problem still remains challenging. In particular, extracting a foreground object in a static image involves determining both full and partial pixel coverage, also known as extracting a matte, which is a severely under-constrained problem. Segmenting spatio-temporal video objects from a video sequence is even harder since extracted foregrounds on adjacent frames must be both spatially and temporally coherent. Previous approaches usually require a large amount of user input and still suffer from inaccurate results and low computational efficiency. This book demonstrates efficient and accurate foreground extraction methods and systems by combining advanced computational algorithms with novel user interfaces. Our systems are capable of extracting high quality foreground objects from images and video with a limited amount of user input such as a few paint strokes of the mouse. We also demonstrate a variety of applications with the extracted foreground objects.Books on Demand GmbH, Überseering 33, 22297 Hamburg 144 pp. Englisch. Artikel-Nr. 9783844390131
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