Micro Baseline Structured Light

Structured light (SL) 3D imaging face a trade-off between acquisition and computational complexity. Multi-shot SL methods need low-complexity computations, but requires projection of several patterns. On the other hand, single-shot methods need only a single pattern, but  computationally expensive decoding. We propose Micro-baseline Structured Light (MSL), a novel approach that needs only a single pattern, with fast decoding. The key theoretical result is a linear version of the non-linear SL image formation equation. Our core contribution is a linear approximation of the SL model leading to an equation in two unknowns (depth and albedo) at each pixel. This result is based on the observation that a small projector-camera baseline leads to small disparities, enabling a first-order approximation of the SL model. The resulting MSL equation is under-constrained due to two unknowns (depth and albedo) at each pixel, but can be efficiently solved using a local least squares approach. We analyze the theoretical and practical performance of the proposed approach in terms of the characteristics of projected patterns. MSL is particularly suited for mobile platforms which require real-time 3D imaging with limited power budget, small size and low-cost components.


Micro-Baseline Structured Light

Viswanath Saradagam, J Wang, Mohit Gupta, Shree Nayar

Proc. ICCV 2019


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