comparison of two algorithms for 3d skin reconstruction
In this paper, a study on 3D skin reconstruction based on image pairs is proposed. To recover 3D skin data from images, two different basic models were focused on. The first model was based on dense matching that combined the feature-based and region-based algorithms to propose a two-stage matching algorithm for a dense map. The second model was based on the Markov Random Field (MRF) model that formulated the problem of 3D reconstruction as a Bayes decision task. It was found that one model is more effective for its corresponding skin texture type. Cross-experiments were done to test the two models with the images that the authors' took. The analysis and comparison are summarized in the algorithms for 3D skin reconstruction.
skin reconstruction dense matching region-based skin texture disparity map mrf model