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

ISBN-13: 9789811082245 / Angielski / Twarda / 2018 / 182 str.

Dominic Ruefenacht

Opis

Key to the success of the proposed "reference-based" anchoring schemes is high quality motion inference, which is enabled by the use of a more "physical" motion representation than the traditionally employed "block" motion fields.

Spis treści

Introduction.- Scalable Image and Video Compression.- Temporal Frame Interpolation (TFI).- Motion-Discontinuity-Aided Motion Field Operations.- Bidirectional Hierarchical Anchoring (BIHA) of Motion.- Forward-Only Hierarchical Anchoring (FOHA) of Motion.- Base-Anchored Motion (BAM).- Conclusions and Future Directions.

O autorze

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.

Blurb

This thesis explores the motion anchoring strategies, which represent a fundamental change to the way motion is employed in a video compression system—from a “prediction-centric” point of view to a “physical” representation of the underlying motion of the scene. The proposed “reference-based” motion anchorings can support computationally efficient, high-quality temporal motion inference, which requires half as many coded motion fields as conventional codecs. This raises the prospect of achieving lower motion bitrates than the most advanced conventional techniques, while providing more temporally consistent and meaningful motion. The availability of temporally consistent motion can facilitate the efficient deployment of highly scalable video compression systems based on temporal lifting, where the feedback loop used in traditional codecs is replaced by a feedforward transform.The novel motion anchoring paradigm proposed in this thesis is well adapted to seamlessly supporting “features” beyond compressibility, including high scalability, accessibility, and “intrinsic” frame upsampling. These features are becoming ever more relevant as the way video is consumed continues to shift from the traditional broadcast scenario with predefined network and decoder constraints to interactive browsing of video content via heterogeneous networks.