Automatic 3D Ear Reconstruction Based on Binocular Stereo Vision

This paper presents an automatic 3D ear reconstruction method based on binocular stereo vision. At first, we calibrate the stereo vision system by Zhang's method. Then the quasi-dense matching method is performed. We use SIFT feature based matching approach and the coarse to fine strategy to compute the seed matches. The adapted match propagation algorithm with known epipolar geometry constraint is used for obtain quasi-dense correspondence points. Finally the 3D ear model can be reconstructed by triangulation and the results are optimized using the bundle adjustment technique. Extensive experimental results have shown that our proposed method can obtain denser 3D ear model than Liu's multi-view based method. It can get sufficient 3D ear points with lower cost and higher efficiency.