Multi-baseline stereo vision for three-dimensional object reconstruction

Three-dimensional object reconstruction is an essential task in many computer applications. In essence, it consists of firstly estimating the disparity of all corresponding points of an observed scene from a pair of stereo images and then determining the depth map of the scene by triangulation from the estimated disparity. Conventionally, the baseline is fixed in general-purpose stereo cameras. This can limit the resolution and robustness of the three-dimensional reconstruction. In this work, a multi-baseline stereo vision approach for three-dimensional object reconstruction is presented. The mathematical principles of multi-baseline stereo vision are provided. Additionally, experimental results of three-dimensional object reconstruction are presented and discussed in terms of objective measures.