Published at: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Sep 2020.
Abstract:
High-quality reconstruction of 3D geometry and texture plays a vital role in providing immersive perception of the real world. Additionally, online computation enables the practical usage of 3D reconstruction for interaction. We present an RGBD-based globally-consistent dense 3D reconstruction approach, accompanying high-resolution (< 1 cm) geometric reconstruction and high-quality (the spatial resolution of the RGB image) texture mapping, both of which work online using the CPU computing of a portable device merely. For geometric reconstruction, we introduce a sparse voxel sampling scheme employing the continuous nature of surfaces in 3D space, reducing more than 95% of the computational burden compared with conventional volumetric fusion approaches. For online texture mapping, we propose a simplified incremental MRF solver, which utilizes previous optimization results for faster convergence, and an efficient reference-based color adjustment scheme for texture optimization. Quantitative and qualitative experiments demonstrate that our online scheme achieves a more realistic visualization of the environment with more abundant details, while taking more compact memory consumption and much lower computational complexity than existing solutions.
Real-time Globally Consistent Dense 3D Reconstruction with Online Texturing
Read More: https://ieeexplore.ieee.org/document/9184935