Tech Report CS-20-01
Fast and Accurate 4D Light Field Depth Estimation
Numair Khan, Min H. Kim and James Tompkin
We present an algorithm for accurate depth estimation from 4D light fi elds that runs almost an order of magnitude faster than classical methods. Our p roposed approach use epipolar-plane image edges to estimate sub-pixel disparity at a small set of pixels in the 4D space. By optimizing constraints at these pix els we are able to diffuse the sparse set in an occlusion-aware manner to obtain dense disparity maps. Qualitative and quantitative results on both synthetic an d real-world light fields show that we have comparable, or better performance th an existing methods, while being significantly faster (8--11x) than current non- learning-based methods.
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