360° video, supporting the ability to present views consistent with the rotation of the viewer's head along three axes (roll, pitch, yaw) is the current approach for creation of immersive video experiences. Nevertheless, a more fully natural, photorealistic experience-with support of visual cues that facilitate coherent psycho-visual sensory fusion without the side-effect of cyber-sickness-is desired. 360° video applications that additionally enable the user to translate in x, y, and z directions are clearly a subsequent frontier to be realized toward the goal of sensory fusion without cybersickness. Such support of full Six Degrees-of-Freedom (6 DoF) for next generation immersive video is a natural application for light fields. However, a significant obstacle to the adoption of light field technologies is the large data necessary to ensure that the light rays corresponding to the viewer's position relative to 6-DoF are properly delivered, either from captured light information or synthesized from available views. Experiments to improve known methods for view synthesis and depth estimation are therefore a fundamental next step to establish a reference framework within which compression technologies can be evaluated. This paper describes a testbed and experiments to enable smooth and artefact-free view transitions that can later be used in a framework to study how best to compress the data.

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This paper describes fixed-point design methodologies and several resulting implementations of the Inverse Discrete Cosine Transform (IDCT) contributed by the authors to MPEG's work on defining the new 8x8 fixed point IDCT standard -ISO/IEC 23002-2. The algorithm currently specified in the Final Committee Draft (FCD) of this standard is also described herein.

We describe a general techniques for improving precision of fixed-point implementations of signal processing algorithms (such as filters, transforms, etc.) by introducing "common factors". These factors are applied to groups of real constants that need to be approximated by dyadic rational numbers, and we show that by carefully choosing values of common factors, the errors of final dyadic rational approximations can be significantly reduced. We show that the problem of design of such approximations is related to the classic Diophantine approximation problem, and include examples explaining how it can be solved, and used for improving practical designs.

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