Image Based 3D Reconstruction of Texture-less Objects for VR Contents

Hafeez, Jahanzeb; Lee, Seung–Hyun; Kwon, Soonchul; Hamacher, Alaric

doi:10.7236/ijasc.2017.6.1.9

Cited by 6 publications

(1 citation statement)

References 21 publications

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“…This is due to the intrinsic characteristics of the instruments, the sensor size and the distance between sensor and object (Bracci et al, 2018). Especially in photogrammetry working with sparse point cloud happens very often, for example when the surface of the object or scene is difficult to reconstruct because is shiny (Delis et al, 2017), texture-less (Hafeez et al, 2017) or curved (Wong & Chan, 2010). The result of point clouds is also affected by bad illumination conditions (Girardeau-Montaut et al, 2005), the thickness of the object and its transparency.…”

Section: Introductionmentioning

confidence: 99%

Improving Performance of Feature Extraction in SFM Algorithms for 3d Sparse Point Cloud

Condorelli

Higuchi

Nasu

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The use of Structure-from-Motion algorithms is a common practice to obtain a rapid photogrammetric reconstruction. However, the performance of these algorithms is limited by the fact that in some conditions the resulting point clouds present low density. This is the case when processing materials from historical archives, such as photographs and videos, which generates only sparse point clouds due to the lack of necessary information in the photogrammetric reconstruction. This paper explores ways to improve the performance of open source SfM algorithms in order to guarantee the presence of strategic feature points in the resulting point cloud, even if sparse. To reach this objective, a photogrammetric workflow is proposed to process historical images. The first part of the workflow presents a method that allows the manual selection of feature points during the photogrammetric process. The second part evaluates the metric quality of the reconstruction on the basis of a comparison with a point cloud that has a different density from the sparse point cloud. The workflow was applied to two different case studies. Transformations of wall paintings of the Karanlık church in Cappadocia were analysed thanks to the comparison of 3D model resulting from archive photographs and a recent survey. Then a comparison was performed between the state of the Komise building in Japan, before and after restoration. The findings show that the method applied allows the metric scale and evaluation of the model also in bad condition and when only low-density point clouds are available. Moreover, this tool should be of great use for both art and architecture historians and geomatics experts, to study the evolution of Cultural Heritage.

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