Z-depth integration: a new technique for manipulating z-depth properties in composited scenes

Kayla Steckel; David Whittinghill

doi:10.1117/12.2044809

28 February 2014 Z-depth integration: a new technique for manipulating z-depth properties in composited scenes

Kayla Steckel, David Whittinghill

Proceedings Volume 9012, The Engineering Reality of Virtual Reality 2014; 90120A (2014) https://doi.org/10.1117/12.2044809
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

This paper presents a new technique in the production pipeline of asset creation for virtual environments called Z-Depth Integration (ZeDI). ZeDI is intended to reduce the time required to place elements at the appropriate z-depth within a scene. Though ZeDI is intended for use primarily in two-dimensional scene composition, depth-dependent “flat” animated objects are often critical elements of augmented and virtual reality applications (AR/VR). ZeDI is derived from “deep image compositing”, a capacity implemented within the OpenEXR file format. In order to trick the human eye into perceiving overlapping scene elements as being in front of or behind one another, the developer must manually manipulate which pixels of an element are visible in relation to other objects embedded within the environment's image sequence. ZeDI improves on this process by providing a means for interacting with procedurally extracted z-depth data from a virtual environment scene. By streamlining the process of defining objects’ depth characteristics, it is expected that the time and energy required for developers to create compelling AR/VR scenes will be reduced. In the proof of concept presented in this manuscript, ZeDI is implemented for pre-rendered virtual scene construction via an AfterEffects software plug-in.

Citation Download Citation

Kayla Steckel and David Whittinghill "Z-depth integration: a new technique for manipulating z-depth properties in composited scenes", Proc. SPIE 9012, The Engineering Reality of Virtual Reality 2014, 90120A (28 February 2014); https://doi.org/10.1117/12.2044809

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KEYWORDS

Cameras

Composites

Virtual reality

3D image processing

Image processing

Eye

Brain

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