Compressed Animated Light Fields with Real-time View-dependent Reconstruction

Koniaris, Charalampos; Kosek, Maggie; Sinclair, David; Mitchell, Kenny

Abstract

We propose an end-to-end solution for presenting movie quality animated graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion. By transforming offline rendered movie content into a novel immersive representation, we display the content in real-time according to the tracked head pose. For each frame, we generate a set of cubemap images per frame (colors and depths) using a sparse set of of cameras placed in the vicinity of the potential viewer locations. The cameras are placed with an optimization process so that the rendered data maximise coverage with minimum redundancy, depending on the lighting environment complexity. We compress the colors and depths separately, introducing an integrated spatial and temporal scheme tailored to high performance on GPUs for Virtual Reality applications. A view-dependent decompression algorithm decodes only the parts of the compressed video streams that are visible to users. We detail a real-time rendering algorithm using multi-view ray casting, with a variant that can handle strong view dependent effects such as mirror surfaces and glass. Compression rates of 150:1 and greater are demonstrated with quantitative analysis of image reconstruction quality and performance.

Citation

Koniaris, C., Kosek, M., Sinclair, D., & Mitchell, K. (2019). Compressed Animated Light Fields with Real-time View-dependent Reconstruction. IEEE Transactions on Visualization and Computer Graphics, 25(4), 1666-1680. https://doi.org/10.1109/tvcg.2018.2818156

• Journal Article Type: Article
• Acceptance Date: Feb 25, 2018
• Online Publication Date: Mar 22, 2018
• Publication Date: Apr 1, 2019
• Deposit Date: Dec 4, 2018
• Publicly Available Date: Dec 5, 2018
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Print ISSN: 1077-2626
• Electronic ISSN: 1941-0506
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 25
• Issue: 4
• Pages: 1666-1680
• DOI: https://doi.org/10.1109/tvcg.2018.2818156
• Keywords: image-based rendering , video compression , light field rendering , multi-view
• Public URL: http://researchrepository.napier.ac.uk/Output/1413552
• Contract Date: Dec 4, 2018