3D face reconstruction using binocular stereo vision

Generation of lifelike 3D human faces is a challenging task.Recent increases in the use of 3D face models in virtual reality,video surveillance,3D animation,and face recognition have led to 3D face reconstruction becoming a research hotspot.The authors proposed a 3D face reconstruction method based on binocular stereo vision theory.After capturing the front view of a face with two calibrated cameras,the captured pair of stereo images were rectified to align their epipolar lines and compensate for image distortions.To obtain maps with accurate matching and dense disparity,a stereo matching algorithm based on region growing was developed.An edge feature point with reliable disparity was selected as a seed point.Then region growing was performed along horizontal scan-lines under multi-constraints.With camera calibration and disparity mapping,3D coordinates of corresponding points were calculated.Then the face model was reconstructed with a series of methods,such as Delaunay triangulation,mesh subdivision and smoothing.Experimental results showed that the method can generate a smooth and lifelike 3D face model.