Three-dimensional (3D) reconstruction using stereo-correlation relates to the automatic extraction of data about the scene's 3D structure from 2 to N images acquired simultaneously. In this context, in order to estimate depth within a scene, the 3D points are triangulated using their projections in the images taken from different viewpoints and the characteristics of the capture system. This chapter introduces the difficulties related to homologue searches as well as primitives and capture geometry. It then examines the generic algorithms of two existing approaches with the most commonly used constraints and costs. In global approaches, the difficult aspects are the initialization of disparities, the choice of the stop conditions, the update of the disparity function and cost, which are dependent on the optimization method used. The chapter concentrates on the occlusion problem by describing two approaches, the first being stereoscopic and the other being multiscopic.