Three-dimensional (3D) geometric model shapes blending method can create various in-between models from two inputs of models shapes. Though, many blended shapes are implausible due to different inputs of model type, inappropriate matching-parts, improper parts-segmentation, and non-tally number of segmentation parts. are crucial and should be taken into account. The objective of this paper is to study the strengths and weaknesses of some prominent shapes blending methods and the 3D reconstruction methods. An interpolated shape blending program using the Laplacian-based contraction and Slinky-based segmentation method is developed to illustrate the critical problems arise in the shape blending process. Output results are to be compared with some prominent existing methods and one will observe the potential research direction in the blending research work