A novel adaptive support window based stereo matching algorithm for 3D reconstruction from 2D images

Three dimensional scene reconstruction, sometimes referred as view synthesis, is a problem in the area of Stereo Vision, which is the most widely used method for gathering depth information from 2D scenes. Stereo vision finds many applications in automated systems such robotics, tracking object in 3D space and constructing a 3D spatial model of a scene. There are many human-machine control applications, such vision based remote control system which exploits stereo vision to control the machine in a touch-free environment. In this paper, we present a new stereo vision matching algorithm using an adaptive support window. In many area based algorithms, the selection and computation of the size and shape of the window is the most crucial factor for obtaining high quality disparity map. We developed an adaptive support window based stereo matching using similar color regions selected by the seed growing algorithm. The proposed approach is tested on Middlebury stereo images and results were promising.