  This paper is based on an application of smoothing of 3D face images followed
by feature detection i.e. detecting the nose tip. The present method uses a
weighted mesh median filtering technique for smoothing. In this present
smoothing technique we have built the neighborhood surrounding a particular
point in 3D face and replaced that with the weighted value of the surrounding
points in 3D face image. After applying the smoothing technique to the 3D face
images our experimental results show that we have obtained considerable
improvement as compared to the algorithm without smoothing. We have used here
the maximum intensity algorithm for detecting the nose-tip and this method
correctly detects the nose-tip in case of any pose i.e. along X, Y, and Z axes.
The present technique gave us worked successfully on 535 out of 542 3D face
images as compared to the method without smoothing which worked only on 521 3D
face images out of 542 face images. Thus we have obtained a 98.70% performance
rate over 96.12% performance rate of the algorithm without smoothing. All the
experiments have been performed on the FRAV3D database.
