Memory Efficient Stereoscopy from Light Fields


We address the problem of stereoscopic content generation from light fields using multi-perspective imaging. Our proposed method takes as input a light field and a target disparity map, and synthesizes a stereoscopic image pair by selecting light rays that fulfill the given target disparity constraints. We formulate this as a variational convex optimization problem.

December 8, 2014
AD International Conference on 3D Vision (3DV) 2014



Changil Kim (Disney Research/ETH Joint PhD)

Ulrich Müller (Disney Research/ETH Joint M.Sc.)

Henning Zimmer (Disney Research)

Yael Pritch (Disney Research)

Alexander Sorkine-Hornung (Disney Research)

Markus Gross (Disney Research/ETH Zürich))

Memory Efficient Stereoscopy from Light Fields


Compared to previous work, our method makes use of multi-view input to composite the new view with occlusions and disocclusions properly handled, does not require any correspondence information such as scene depth, is free from undesirable artifacts such as grid bias or image distortion, and is more efficiently solvable. In particular, our method is about ten times more memory efficient than the previous art, and is capable of processing higher resolution input. This is essential to make the proposed method practically applicable to realistic scenarios where HD content is standard. We demonstrate the effectiveness of our method experimentally.

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