  Mesh plays an indispensable role in dense real-time reconstruction essential
in robotics. Efforts have been made to maintain flexible data structures for 3D
data fusion, yet an efficient incremental framework specifically designed for
online mesh storage and manipulation is missing. We propose a novel framework
to compactly generate, update, and refine mesh for scene reconstruction upon a
volumetric representation. Maintaining a spatial-hashed field of cubes, we
distribute vertices with continuous value on discrete edges that support O(1)
vertex accessing and forbid memory redundancy. By introducing Hamming distance
in mesh refinement, we further improve the mesh quality regarding the triangle
type consistency with a low cost. Lock-based and lock-free operations were
applied to avoid thread conflicts in GPU parallel computation. Experiments
demonstrate that the mesh memory consumption is significantly reduced while the
running speed is kept in the online reconstruction process.
