This paper presents a volumetric method for integrating range images to reconstruct complex surfaces. The method combines signed distance functions and weight functions to represent the uncertainty in range data, allowing for incremental updating, robustness in the presence of outliers, and the ability to fill gaps in the reconstruction. The core of the algorithm involves scanning each range image to a distance function, combining it with existing data using an additive scheme, and representing the cumulative signed distance and weight functions on a discrete voxel grid. The final surface is extracted by finding the isosurface of the cumulative signed distance function. The method is efficient due to run-length encoding of the voxel grid and synchronized processing of voxel and resampled range image scanlines. The authors demonstrate the effectiveness of their method through various examples, including a thin drill bit and a dragon model, showing that it can generate high-resolution, hole-free models suitable for rendering and rapid prototyping. The paper also discusses limitations and future work, such as improving execution time and parallelization.This paper presents a volumetric method for integrating range images to reconstruct complex surfaces. The method combines signed distance functions and weight functions to represent the uncertainty in range data, allowing for incremental updating, robustness in the presence of outliers, and the ability to fill gaps in the reconstruction. The core of the algorithm involves scanning each range image to a distance function, combining it with existing data using an additive scheme, and representing the cumulative signed distance and weight functions on a discrete voxel grid. The final surface is extracted by finding the isosurface of the cumulative signed distance function. The method is efficient due to run-length encoding of the voxel grid and synchronized processing of voxel and resampled range image scanlines. The authors demonstrate the effectiveness of their method through various examples, including a thin drill bit and a dragon model, showing that it can generate high-resolution, hole-free models suitable for rendering and rapid prototyping. The paper also discusses limitations and future work, such as improving execution time and parallelization.