Fusion of Heterogeneous Range Sensors Dataset for High Fidelity Surface Generation

Abstract

Due to the need for higher quality depth data than possible with an individual range sensing approach nowadays, there has been a growing interest to develop an integrated depth sensing technique by fusion of different $3D$ acquisition approaches that are more precise than the individual devices. In this paper, a new unsupervised range data fusion method using distinct range sensors has been presented for the extraction of an accurate surface model. In the fusion method, the analysis of Kinect's depth data based on Haar wavelets is used to identify regions requiring finer scan by the Laser range sensor. The fused data illustrate the more accurate descriptive characteristic of the surface. The experimental results show a high quality reconstructed $3D$ model which validates the correctness of the real surfaces.