ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-5-2024
https://doi.org/10.5194/isprs-annals-X-5-2024-17-2024
https://doi.org/10.5194/isprs-annals-X-5-2024-17-2024
11 Nov 2024
 | 11 Nov 2024

Accuracy Assessment of an Image-Based Cloud-Based Indoor Mapping Platform as an Alternative for Desktop Applications

Alexis Richard C. Claridades and Denrazir M. Atara

Keywords: Omnidirectional Image, Indoor Space Modeling, Cloud-based Processing, Image-based Navigation

Abstract. The generation of 3D spatial datasets, especially in indoor space, has continually been a challenge in developing spatial applications that are aimed for the realistic representation of the real world. Despite their potential, the creation of 3D spatial data remains a challenge, particularly in terms of cost and complexity associated with traditional methods. While this method proves to be a reliable and accurate method of creating such data, this approach entails challenges in economic, computational, and human resource aspects. Alternatively, omnidirectional images have emerged as cost-effective alternatives for representing 3D spaces, offering a comprehensive field of view and facilitating the generation of structure and appearance representations through mesh-based 3D maps. This study evaluates the geometric accuracy of a cloud-based image-based mapping platform for generating 3D representations of indoor spaces, aiming to assess its suitability as an alternative to desktop-based platforms. We obtained 30 sample lines and compare respective measurements from each of the generated meshes to a ground truth value. Results show that while there are no significant differences in the mean errors, the mesh generated from a cloud-based platform produced minimal errors. This demonstrates the potential of this platform for generating 3D representations of indoor space, acceptable in both geometric accuracy and visualization capabilities.