## 3 Low-Cost Digitisation for VR E-Commerce
### 3D Model Quality Evaluation
For the rest of the models, it can be observed that, except on one occasion, the results of the models obtained with Polycam using photogrammetry indicate greater precision compared to the models obtained with LiDAR sensors. Regarding the models obtained by photogrammetry, the average of the RMS results indicates a 2.36 cm difference in the measured distances. Figure 5: Comparison of 3D models performed using CloudCompare 2.9.3. (**a**) High-poly shoes as reference and low-poly shoes as compared; (**b**) High-poly teddy as reference and Polycam in Android’s version teddy as compared. Figure 6: High-poly and low-poly meshes generated by Luma AI from one of the objects. By inspecting the CMDM results obtained, we can see that medium-poly models achieved the best results overall, with an average perceived distortion of 13.22% considering all comparisons. Only in the case of the mushroom did another comparison achieve better results, which was the one between Polycam models, the reference model being that from the Android version. However, this was the model that obtained the least realistic results due to the material it is made of. Again, the object that achieved the best results in both applications was the burner. It is interesting to note that the difference in perceived distortion between medium-poly and low-poly results is on average 3.4%, which indicates really good quality for low-poly models as well. This metric also shows the overall low capability of LiDAR sensors to provide good visual quality results when scanning moderate-sized objects. Having analysed the obtained data, we can conclude that the use of LiDAR sensors with the Polycam application should not be the preferred option for obtaining realistic 3D models that can be showcased in VR shopping environments. The various metrics employed have yielded the worst visual quality level results for these models, both in comparisons using a reference model and those without. Therefore, for obtaining a realistic 3D model, the preferred option would be NeRF, specifically in the form of a mobile application like Luma AI, when available on a device. The data from the metrics used, both with and without a reference model, show that the models from Luma AI have the highest visual quality, except in NR-3 DQA in the case of sports shoes. Taking into account high-poly models, values between 5 and 20% higher were obtained compared to the photogrammetry application used. Considering low-poly models, this range is reduced to between 2 and 15%. Given the visual results of the photogrammetry application, and considering that the difference is not very large in the results, this option is also viable for obtaining high visual quality 3D models that can be used in VR. Figure 7: Comparison of details between Luma AI low-poly model, Polycam from Xiaomi, Polycam from iPad and the real object. (**a**) Shoe model generated with Xiaomi phone (Polycam); (**b**) Shoe low-poly model generated with Luma AI; (**c**) Shoe model generated with iPad (Polycam); (**d**) Shoes in real life. Discussion  
Our evaluation revealed that the difference in visual quality between Luma AI models and those obtained through photogrammetry was generally minor, ranging from 10% to 20%. Specifically, the Root Mean Square (RMS) values for the medium-poly models of Luma AI were as low as 0.00041, while Polycam's photogrammetry models showed slightly higher RMS values of approximately 0.01269 for the optimised models. However, the difference with models obtained using LiDAR sensors was significantly greater, with some cases showing RMS differences up to 70% higher, such as the RMS value of 0.05976 for low-poly models. This substantial disparity leads us to consider the models produced by Luma AI as having the highest visual quality among the technologies we tested. As such, we recommend Luma AI for product digitisation when the highest visual fidelity is required. Additionally, Luma AI provides comprehensive support for NeRF technology, which is critical for achieving high-quality 3D models.