Face recognition using 3D faces has become widely popular in the last few years due to its ability to overcome recognition problems encountered by 2D images. An important aspect to a 3D face recognition system is how to represent the 3D face image. In this chapter, it is proposed that the 3D face image be represented using adaptive non-uniform meshes which conform to the original range image. Basically, the range image is converted to meshes using the plane fitting method. Instead of using a mesh with uniform sized triangles, an adaptive non-uniform mesh was used instead to reduce the amount of points needed to represent the face. This is because some parts of the face have more contours than others, hence requires a finer mesh. The mesh created is then used for face recognition purposes, using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Simulation results show that an adaptive non-uniform mesh is able to produce almost similar recognition rates compared to uniform meshes but with significant reduction in number of vertices. © 2012, IGI Global.
|Title of host publication||Depth map and 3D imaging applications|
|Subtitle of host publication||Algorithms and technologies|
|Editors||Aamir Saeed Malik, Tai Sun Choi, Humaira Nisar|
|Place of Publication||Hershey, Pa.|
|Number of pages||12|
|ISBN (Print)||9781613503263, 9781613503287|
|Publication status||Published - 2012|