In this paper, the author presents a work on i) range data and ii) stereo-vision system based disparity map profiling that are used as signatures for 3D face recognition. The signatures capture the intensity variations along a line at sample points on a face in any particular direction. The directional signatures and some of their combinations are compared to study the variability in recognition performances. Two 3D face image datasets namely, a local student database captured with a stereo vision system and the FRGC v1 range dataset are used for performance evaluation.
|Title of host publication||2013 IEEE International Conference on Systems, Man, and Cybernetics|
|Number of pages||6|
|Publication status||E-pub ahead of print - 27 Jan 2014|