Affiliation:
1. Jadavpur University, India
Abstract
Although, automatic face recognition has been studied for more than four decades; there are still some challenging issues due to different variations in face images. There are mainly two categories of face recognition based on acquisition procedure. One technology that deals with video based face recognition and another approach where different sensors are used for acquisition purpose of different stationary face images, for instance: optical image, infra-red image and 3D image. In this context, researchers have focused only on 3D face images. 3D face images convey a series of advantages over 2D i.e. video frame, optical as well as infra-red face images. In this chapter, a detailed study of acquisition, visualization, detail about 3D images, analyzing it with some fundamental image processing techniques and application in the field of biometric through face registration and recognition are discussed. This chapter also gives a brief idea of the state of the art about the research methodologies of 3D face recognition and its applications.
Reference73 articles.
1. Adaptive Registration for Occlusion Robust 3D Face Recognition
2. BU3D database. (n.d.). Retrieved 22nd July, 2014, from http://www.cs.binghamton.edu/~lijun/Research/3DFE/3DFE_Analysis.html
3. Bagchi, P., Bhattacharjee, D., Nasipuri, M., & Basu, D. K. (2012). A Novel approach to nose-tip and eye-corners detection using H-K Curvature Analysis in case of 3D images. Proc of International Journal of Computational Intelligence and Informatics, 2(1).
4. Bagchi, P., Bhattacharjee, D., Nasipuri, M., & Basu, D. K. (2013). A Method for Nose-tip based 3D face registration using Maximum Intensity algorithm. In IEEE international Conference of Computation and Communication Advancement.
5. Berretti, S., Bimbo, A., & Pala, P. (2013). Sparse Matching of Salient Facial Curves for Recognition of 3-D Faces with Missing Parts. IEEE Transactions on Information Forensics and Security, 8(2), 374-389.