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This paper is based on an application of smoothing of 3D face images followedby feature detection i.e. detecting the nose tip. The present method uses aweighted mesh median filtering technique for smoothing. In this presentsmoothing technique we have built the neighborhood surrounding a particularpoint in 3D face and replaced that with the weighted value of the surroundingpoints in 3D face image. After applying the smoothing technique to the 3D faceimages our experimental results show that we have obtained considerableimprovement as compared to the algorithm without smoothing. We have used herethe maximum intensity algorithm for detecting the nose-tip and this methodcorrectly 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 faceimages as compared to the method without smoothing which worked only on 521 3Dface images out of 542 face images. Thus we have obtained a 98.70% performancerate over 96.12% performance rate of the algorithm without smoothing. All theexperiments have been performed on the FRAV3D database.

A novel approach for nose tip detection using smoothing by weighted median filtering applied to 3D face images in variant poses