Abstract

Abstract., This paper investigate how motion between two images is affecting the reconstruction process of the KLT algorithm which we used to convert 2D images to 3D model. The reconstruction process is carried out using a single calibrated camera and an algorithm based on only two views of a scene, the SFM technique based on detecting the correspondence points between the two images, and the Epipolar inliers. Using the KLT algorithm with structure from motion method shows the incompatibility of it with the widely-spaced images. Also, the ability of reducing the rate of reprojection error by removing the images that have the biggest rate of error. The experimental results are consisting from three stages. The first stage is done by using a scene with soft surfaces, the performance of the algorithm shows some deficiencies with the soft surfaces which are have few details. The second stage is done by using different scene with objects which have more details and rough surfaces, the algorithm results become more accurate than the first scene. The third stage is done by using the first scene of the first stage but after adding more details for surface of the ball to motivate the algorithm to detect more points, the results become more accurate than the results of the first stage. The experiments are showing the performance of the algorithm with different scenes and demonstrate the way of improving the algorithm where it found more points from images, so it builds more accurate 3D model.

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