Multi-view Range Images Integration Based On A Generalized Iso-surface Equation

One of the important issues in implicit surface modeling is the construction of an iso-surface equation for the application of multi-view range image integration. Once such an equation is built, the algorithm can be designed to extract iso-surface from it, which involves in providing a solution for the equation. In this article, we propose a method to construct a generalized iso-surface equation (GIE), which is based on vector-map reasoning and least-mean-square approximation. In this approach, we introduce the directional information into the equation from which one is able to build up a clear geometrical or physical picture to explain the relationship between the weight function and signed-distance. This result has generalized the equation obtained by Curless . Under the constrained condition, the generalized iso-surface equation can be simplified to the Curless equation. We also apply the GIE to merge multi-view range images. Experimental results are also presented.