The reconstruction of scenes from imagens has received special attention from researchers of the areas of computer vision, computer graphics and geometric modeling. As examples of application we can mention image-based scene reconstruction, modeling of complex as-built objects, construction of virtual environments and telepresence. Among the most successful methods used for the reconstruction of scenes from images are those based on Space Carving algorithms. These techniques reconstruct the shape of the objects of interest in a scene by determining, in a volumetric representation of the scene space, those elements that satisfy a set of photometric constraints imposed by the input images. Once determined, each photo- consistent element is colorized according to the photometric information in the input images, in such a way that they reproduce the photometric information in the input images, within some pre-specificied error tolerance. In this work, we investigate the use of rendering techniques in space carving methods. As a result, we propose a method based on an adaptive refinement process which works on reconstruction spaces represented by spatial subdivisions. We claim that such method can reconstruct the objects of interest in a more efficient way, using resources proportional to the local characteristics of the scene, which are discovered as the reconstruction takes place. Finally, we evaluate the quality and the efficiency of the method based on the results obtained from a reconstruction device that works with images captured from webcams.