Fusion of 3 D Shapes in Multiple View Points to Obtain More Accurate Shape

Abstract

The aim of this paper is to obtain an exact 3 D model of a scene using multiple images from different camera positions. The reconstruction of 3 D shape using two images has problem such as being weak at noise. Therefore we present methods to reduce noise and to improve the accuracy of 3 D shape with multiple images. The system is divided into three stages: firstly, reconstruction of 3 D shapes at different camera positions, secondly fusing the 3 D shapes to obtain a para-ideal shape, and thirdly removing the outlier shapes and feature points by evaluation function, and fusing the rest of shapes. Even though the corruption of image data by noise is one of the unavoidable problems in any system, this paper shows how well the noise is removed by the proposed algorithms in multiple view points. We demonstrate a significant improvement of recovered shape. Experimental results show that our system performs well to remove noise with robustness. The maximum noise reduction rate is 82% in the real image experiment.