Recent technological advances in computer vision and the advent of commercial RGB-D sensors have certainly boosted 3D modeling applications. This work presents an integrated system that enables the digitization of big objects, like vehicles, with low-cost RGB-D sensors. The implemented system can be used for visualization and monitoring of vehicles in large fleets that currently require a time-consuming manual inspection process. The main objective is to achieve an efficient consolidation of multiple views of a vehicle inside a moving frame, to acquire color and depth data and generate its 3D representation. The proposed integrated system denoises the acquired depth maps, aligns the produced point clouds captured in different time instances, and builds the 3D-reconstructed mesh. Finally, we apply a texture mapping algorithm to acquire realistic texture details and remove any visible seams. We evaluate all modules of the implemented system by performing several experiments with scanned vehicles.

计算机视觉的最新技术进步以及商用RGB-D传感器的出现无疑促进了3D建模应用。这项工作提出了一个集成系统，该系统可以使用低成本RGB-D传感器对大型物体（例如车辆）进行数字化。所实施的系统可用于可视化和监视大型车队中的车辆，这些车辆目前需要耗时的手动检查过程。主要目标是在移动框架内实现车辆多个视图的有效合并，以获取颜色和深度数据并生成其3D表示。拟议的集成系统对获取的深度图进行降噪，对齐在不同时间实例中捕获的生成的点云，并构建3D重构的网格。最后，我们应用纹理映射算法来获取逼真的纹理细节并消除任何可见的接缝。我们通过对扫描的车辆进行几次实验来评估实施系统的所有模块。