Low-density point eating algorithm for surface reconstruction from dense scans.

We present a low-density point eating algorithm for surface reconstruction from dense scans. First, the density map for each scan is estimated and the boundary densities are down-weighted. Subsequently, the poorly scanned low-density overlapping points are eaten up based on a user-specified threshold.

Exposure-fusion-based dot-grid image acquisition and recognition for sheet metal strain analysis.

Dot-grid images are usually captured for grid strain analysis during sheet metal forming. Due to the strong reflective characteristic of the metallic surfaces, the recorded dot-grid images often have poor quality, low positioning accuracy, and low recognition rate. Therefore, an exposure-fusion-based dot-grid image acquisition and recognition approach is proposed.

Guide to quickly build high-quality three-dimensional models with a structured light range scanner.

In literature, there are many reports about how to build high-precision, high-speed, and/or flexibly structured light range scanners. Whereas, there are few papers reported about how to implement the scanning to reach the full potential of the scanners when digitizing various objects. In this paper, some scanning strategies adopted by the structured light range scanner XJTUOM are introduced.

Density adaptive trilateral scan integration method.

We present a trilateral scan integration method to extract a desirable single-layer, smooth, detailed point set surface. A density adaptive overlapping areas detection algorithm is developed to detect overlapping points in raw scans. Subsequently, a variant trilateral filter is designed to shift the overlapping points to a single layer surface as well as reduce noises and outliers.