High-Quality and Memory-Efficient Volumetric Integration of Depth Maps Using Plane Priors

Yangdong Liu, Wei Gao, Zhanyi Hu

Abstract: Volumetric integration method is widely used to fuse depth maps in dense 3D reconstruction systems. High memory footprint is one of its main disadvantages. We introduce a method to de-noise depth maps and save memory usage during volumetric integration of depth maps with the use of plane priors. We develop a new planar region detection method with the use of depth gradients and then de-noise the planar region of depth maps. During volumetric integration we allocate the voxels and integrate depth maps with the use of plane priors as well. Extensive experiments show that our method saves approximately 30% memory footprint and has higher reconstruction quality compared with some of the current state-of-the-art systems. These characteristics enable our method to be used for 3D scanning on mobile devices which have limited memory resources.