Abstract
As an important research topic in the field of computer vision, 3D modeling of complex scene has an extensive application prospect. RGB-D sensor has been widely used to obtain the depth information in recent years. However, the existing processing system is simply suitable for small-scale scene modeling. In order to develop a better algorithm for large-scale complex scene modeling, this paper builds a 3D scene reconstruction system based on RGB-D images, achieving a better performance in accuracy and real time. SIFT algorithm is first to extract key points to match the descriptors between consecutive frames. By converting into three-dimensional space through the intrinsic matrix, the effective pixel points in the images are then reintegrated to establish the spatial point clouds model which is finally optimized by RANSAC algorithm. The experiments are based on the public database and propose the solution of the problems in the system, which provides a platform for basic research work.
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Acknowledgments
The research is supported partially by the Natural Science Foundation of China under Contract 61672079, 61473086. The work of B. Zhang is supported partially by the Program for New Century Excellent Talents University within the Ministry of Education, China, as well by the Beijing Municipal Science and Technology Commission under Grant Z161100001616005.
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Wang, H., Wang, P., Wang, X., Peng, T., Zhang, B. (2018). A 3D Reconstruction System for Large Scene Based on RGB-D Image. In: Peng, Y., Yu, K., Lu, J., Jiang, X. (eds) Intelligence Science and Big Data Engineering. IScIDE 2018. Lecture Notes in Computer Science(), vol 11266. Springer, Cham. https://doi.org/10.1007/978-3-030-02698-1_45
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DOI: https://doi.org/10.1007/978-3-030-02698-1_45
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