Low-Cost Real-Time 3D Reconstruction of Large-Scale Excavation Sites using an RGB-D Camera

Zollhöfer, Michael; Siegl, Christian; Riffelmacher, B.; Vetter, Michael; Dreyer, Boris; Stamminger, Marc; Bauer, Frank

doi:10.2312/gch.20141298

Cited by 2 publications

(1 citation statement)

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“…Also, they did not use Super-Resolution to improve captures from low-cost devices, and the models produced by the Kinect lack any color information. Zollhöfer et al (2014) used a Kinect sensor to capture the geometry of an excavation site and took advantage of a topographic map to distort the reconstructed model, significantly increasing the quality of the scene. The global distortion, with Super-Resolution techniques applied to raw scans, significantly increased the fidelity and realism of its results but is too specialized for large scale-scenes.…”

Section: Introductionmentioning

confidence: 99%

Improved low-cost 3D reconstruction pipeline by merging data from different color and depth cameras

Silva¹,

Aguero²

2022

RBCA

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The performance of traditional 3D capture methods directly influences the quality of digitally reconstructed 3D models. In order to obtain complete and well-detailed low-cost three-dimensional models, this paper proposes a 3D reconstruction pipeline using point clouds from different sensors, combining captures of a low-cost depth sensor post-processed by Super-Resolution techniques with high-resolution RGB images from an external camera using Structure from Motion and Multi-View Stereo output data. The main contribution of this work includes the description of a complete pipeline that improves the stage of information acquisition and merges data from different sensors. Several phases of the 3D reconstruction pipeline were also specialized to improve the model's visual quality. The experimental evaluation demonstrates that the developed method produces good and reliable results for low-cost 3D reconstruction of an object.

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Section: Introductionmentioning

confidence: 99%