Multi-resolution 3D reconstruction of cultural landscape heritage based on cloud computing and hd image data

Issue title: Special Section: Intelligent Algorithms for Complex Information Services - Recent Advances and Future Trends

Guest editors: Andino Maseleno, Xiaohui Yuan and Valentina E. Balas

Article type: Research Article

Authors: Zhang, Long^a | Liu, Leyi^a | Chai, Bailong^a | Xu, Man^a | Song, Yuhong^{a; b; *}

Affiliations: [a] College of Landscape Architecture and Horticulture Science, Southwest Forestry University, Kunming, Yunnan, China | [b] Southwest Landscape Architecture Engineering Technology Research Center of the National Forestry and Grassland Administration, Kunming, Yunnan, China

Correspondence: [*] Corresponding author. Yuhong Song, College of Landscape Architecture and Horticulture Science, Southwest Forestry University, Kunming 650224, Yunnan, China. E-mail: songyuhong@swfu.edu.cn.

Abstract: Cultural landscapes are cultural property and they are an illustration of the evolution of human society and the living environment over time. As cultural landscape is being valued more and more, the use of 3D modeling is becoming more and more important. As for the 3D reconstruction technology, most of the current methods are complicated in terms of network construction, use, and storage, and then affect the reconstruction efficiency of subsequent cultural landscape heritage. To obtain the 3D reconstruction technology with high reconstruction efficiency, this paper combines the circumferential binary feature extraction algorithm and cloud computing technology, and proposes a circumferential binary feature extraction and matching search method. The interior-point rate of the CBD algorithm in this paper is greater than 72%, which is higher than the interior point rate of other different algorithms, which indicates that the CBD algorithm in this paper is suitable for matching HD rotated images. The experimental results show that the circular binary features extracted by the article have strong adaptability and fast contrast rate. To better the 3D reconstruction of cultural landscape heritage in the later period, this paper also improves the 4PSC point cloud rough registration algorithm. The experimental results show that compared with other coarse registration algorithms, the improved point cloud coarse registration algorithm improves the registration accuracy and the registration effect is good, which proves the effectiveness of the algorithm.

Keywords: Cloud computing technology, 3D reconstruction, circular binary feature extraction, high-definition image data, point cloud coarse registration, cultural landscape

DOI: 10.3233/JIFS-179995

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5097-5107, 2020