Variance and Symmetrical-based Approach for Optimal Alignment of 3D Model

The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer’s world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object’s point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.