Implementing bezier surface interpolation and N.N in shape reconstruction and depth estimation of a 2D image.

Abstract

This paper considers a 2D image depth estimation of an object and reconstructed it into a 3D object image. The 2D image is defined by slices contains asset of points that are located along the object contours and within the object body. The depth of these slices are estimated using the neural network technique (N.N), where five factors (slice length, angle of incident light and illumination of some of point that located along the 2D object, namely control points)are used as inputs to the network the estimated depth of the slice are mapped into a 3D surface using the interpolation technique of the Bezier spleen surface. The experimental results showed an effective performance of the proposed approach.