3D FACE RECOGNITION AND MODELING SYSTEM

In this paper, 2D photographs image divided into two parts; one part is front view (x, y) and side view (y, z). Necessary condition of this method is that position or coordinate of both images should be equal. We combine both images according to the coordinate then we will get 3D Models (x, y, z) but this 3D model is not accurate in size or shape. In defining other words, we will get 3D face model, refinement of 3D face through edit of point and smoothing process. Smoothing is performed to get the more realistic 3D face model for the person. We measure to compare the average time for modeling and compare the research result of our methods with different techniques, for this purpose we taken by two hypotheses (1) the average quality of our method will be higher than the 60% (2) it is faster compare to other in an average case (3) it is automated. First hypothesis is correct but the second tie up with other three methods and third found satisfactory.

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