关键词: 多视场景, 三维目标, 贝叶斯推理, 变分分割, 水平集

Abstract: In order to solve the problems that exist in 3D segmentation reconstruction given a series of images from calibrated cameras, a variational method based on probabilistic formulation was proposed. First, through computing most probable surface that gave rise to the images, a 3D surface consistent with these segmentations was built. Then, through fusing joint probabilities, the mean intensity and variance of the extracted object and background were reconstructed. At last, by using a level set framework, the numerical implementation of surface energy equation was carried out. The proposed method can reconstruct complex topologies and cope with noisy data. Compared to carving techniques and stereoscopic segmentation, the experimental results show the effectiveness and robustness of the method with segmentation and reconstruction of arbitrary 3D objects.

Key words: Multiple-views scenes, 3D objects, Bayesian inference, Variational segmentation, Level set