A method for nose-tip based 3D face registration using maximum intensity algorithm
This addresses pose alignment in 3D face recognition, but it is incremental as it builds on existing registration methods.
The paper tackles 3D face registration across pose by determining rotation angles and performing translation, achieving a 75.84% performance rate on 472 images from the FRAV3D database.
In this paper we present a novel technique of registering 3D images across pose. In this context, we have taken into account the images which are aligned across X, Y and Z axes. We have first determined the angle across which the image is rotated with respect to X, Y and Z axes and then translation is performed on the images. After testing the proposed method on 472 images from the FRAV3D database, the method correctly registers 358 images thus giving a performance rate of 75.84%.