Abstract
The fast evolution in computational and sensor technologies brings previously niche solutions to a wider userbase. As such, 3D reconstruction technologies are reaching new use-cases in scientific and everyday areas where they were not present before. Cost-effective and easy-to-use solutions include camera-based 3D scanning techniques, such as photogrammetry. This paper provides an overview of the available solutions and discusses in detail the depth-image based Real-time Appearance-based Mapping (RTAB-Map) technique as well as a smartphone-based solution that utilises ARCore, the Augmented Reality (AR) framework of Google. To qualitatively compare the two 3D reconstruction technologies, a simple length measurement-based method was applied with a purpose-designed reference object. The captured data were then analysed by a processing algorithm. In addition to the experimental results, specific case studies are briefly discussed, evaluating the applicability based on the capabilities of the technologies. As such, the paper presents the use-case of interior surveying in an automated laboratory as well as an example for using the discussed techniques for landmark surveying. The major findings are that point clouds created with these technologies provide a direction- and shape-accurate model, but those contain mesh continuity errors, and the estimated scale factor has a large standard deviation.
Highlights
Before the focus can be set on two specific widely available technologies, the big picture of three-dimensional (3D) reconstruction approaches has to be presented
The subject of these works, are all fixed-frame imaging techniques. These deliver depth images in a known coordinate system, in which the ranges can explicitly be determined. Both in the case of RTAB-Map and ARCore, the resulting point cloud or mesh is generated based on images (RGB or RGB-D) from multiple angles, i.e., from different coordinate frames
One can see that these technologies alone cannot replace more advanced 3D scanning apparatus, i.e., Time of Flight (ToF) light detection and ranging (LiDAR), but they can be utilised in various use-cases where lower quality but quickly-generated models are applicable
Summary
Before the focus can be set on two specific widely available technologies, the big picture of three-dimensional (3D) reconstruction approaches has to be presented. 3D reconstruction is one of the most complex forms of optical sensing, in that it is derived through multiple steps from simpler sensing techniques [1]. Optical sensors are a diverse group of measuring devices, the operation of which is based on retrieving information with the help of the visible spectrum of the electromagnetic waves (referred to as light). This is sometimes extended with the infrared and the ultraviolet spectra. Each step of deriving a method from a simpler one is denoted by the type of augmentation. Single units can either be combined into vectors or arrays, or they can be given additional degrees-of-freedom by movement
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