Abstract
In the context of three-dimensional acquisition and elaboration, it is essential to maintain a balanced approach between model accuracy and required resources. As a possible solution to this problem, the present paper proposes a method to obtain accurate and lightweight meshes of a real environment using the Microsoft® HoloLens™ as a device for point clouds acquisition. Firstly, we describe an empirical procedure to improve 3D models, with the use of optimal parameters found by means of a genetic algorithm. Then, a systematic review of the indexes for evaluating the quality of meshes is developed, in order to quantify and compare the goodness of the obtained outputs. Finally, in order to check the quality of the proposed approach, a reconstructed model is tested in a virtual scenario implemented in Unity® 3D Game Engine.
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Trotta, G.F., Mazzola, S., Gelardi, G., Brunetti, A., Marino, N., Bevilacqua, V. (2020). Reconstruction, Optimization and Quality Check of Microsoft HoloLens-Acquired 3D Point Clouds. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore. https://doi.org/10.1007/978-981-13-8950-4_9
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