Reliable landmarks as anchors for 3D face reconstruction

Abstract—A way to create a 3D reconstruction of a face is using a 5 camera setup. In this paper a method is presented for finding reliable landmarks in the five 2D images of the face that serve as anchor points to improve the 3D reconstruction. The method consist of four parts that all aid in finding more correct points. The four parts are: 1. Finding candidate points using the SURF algorithm, 2. Matching the points based on the global location of the point, 3. Rejecting poor-matched points by detecting outliers and by using the a multiscale Local Binary Pattern (LBP) algorithm, and 4. Combining all points in all five images. The best results are found for a number of candidate SURF point of 10, and a LBP threshold of D2 and D3: sufficient points are found and the points are well-distributed over the face. An increase in threshold results in both more correct and wrong points. The performance of the method depends also on the subject (facial hair, fair faces), the use of glasses and whether the subject is right in front of the camera or slightly skew. Further improvements on the performance can be achieved by improving parts of the method and optimizing other parameters