Genetic algorithms and bundle adjustment for the enhancement of 3D reconstruction
- PDF / 7,679,846 Bytes
- 24 Pages / 439.37 x 666.142 pts Page_size
- 50 Downloads / 226 Views
Genetic algorithms and bundle adjustment for the enhancement of 3D reconstruction B. Satouri 1 & K. Satori 1 & A. El abderrahmani 2 Received: 18 June 2019 / Revised: 13 March 2020 / Accepted: 22 May 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
In this paper, we present a new technique of tridimensional reconstruction from a sequence of uncalibrated stereo images taken with cameras having varying parameters. At first, our system allows to recover initial coordinates of a set of 3D points. In this context, we have used our method of self-calibration based on the use of unknown 3D scene with its image projections and genetic algorithms to estimate all intrinsic parameters. After that extrinsic parameters are estimated based on classical pose estimation algorithms. Matching points and estimated value of intrinsic and extrinsic parameters are used to estimate initial 3D model that helps us in the initialization step. In order to have a reliable and relevant 3D reconstruction the proposed method is based on good and new exploitation of bundle adjustment (without camera poses initialization) technique based on Levenberg-Marquardt optimization with the aim to estimate our optimal 3D model that has special features compared to the classical case because it masks the pose parameters estimation in the optimization process. Finally, 3D mesh of the 3D scene is constructed with Delaunay algorithm and the 2D image is projected on the 3D model to generate the texture mapping. Experiments is conducted on real data to achieve demonstrate the validity and the performance of the proposed approach in terms of convergence, simplicity, stability and reconstruction quality. Keywords 3D reconstruction . Bundle adjustment . Self-calibration . Interests points . Matching . 3D mesh * B. Satouri [email protected] K. Satori [email protected] A. El abderrahmani [email protected]
1
LIIAN, Department of Mathematics and Informatics, Faculty of Sciences Dhar-Mahraz, P.O.Box 1796, Atlas Fes, Morocco
2
LIIAN, Department of Mathematics and Informatics, Larache Poly disciplinary School, Larache, Morocco
Multimedia Tools and Applications
1 Introduction 3D reconstruction [1, 18–21, 28, 34, 45, 46] is one of the most popular research areas in computer vision and computer graphics, it is widely used in many fields, such as video game, animation and so on. It consists in recovering three-dimensional information from 2D images (taken from different viewpoints) or from videos. Using this technology, we can implement scene recurrence, observe the model from any viewpoints stereoscopically and perceive the world well. With the development of computer technology and the increase of digitalizing demand, we hope to break the computers information processing ability and turn it to intellectively process multi-dimensional information. The principle of 3D reconstruction is always to extract information on the threedimensional scene from a sequence of images taken by numerical cameras with different viewpo
Data Loading...
