Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression

Author:   Dominic Rüfenacht
Publisher:   Springer Verlag, Singapore
Edition:   Softcover reprint of the original 1st ed. 2018
ISBN:  

9789811340970


Pages:   182
Publication Date:   10 January 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression


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Author:   Dominic Rüfenacht
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   Softcover reprint of the original 1st ed. 2018
Dimensions:   Width: 15.50cm , Height: 1.10cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9789811340970


ISBN 10:   9811340978
Pages:   182
Publication Date:   10 January 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Dominic Ruefenacht received his B.Sc. and M.Sc. in Communication Systems with a specialization in ‘Signals, Images and Interfaces’ from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, in 2009 and 2011. He was an exchange student at the University of Waterloo, Ontario, Canada, and did his Master's thesis at Philips Consumer Lifestyle in Eindhoven, Netherlands. He obtained his Ph.D. degree from UNSW Sydney, Australia, in 2017, where he was investigating “Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression”. From 2011 to 2013, he was with the Image and Visual Representation Group (IVRG) at EPFL as a research engineer, where he was working on computational photography problems, with emphasis on near-infrared imaging. He currently holds a post-doctoral position at UNSW Sydney, working on next-generation video compression systems. His research interests are in computational photography and highly scalable and accessible video compression, with a focus on temporal scalability.

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