Real-time acquisition and super-resolution techniques on 3D reconstruction

This work proposes to improve a traditional 3D reconstruction pipeline by combining it with two techniques: A realtime 3D modelling system to give a visual feedback in acquisition stage; and a super-resolution spatio-temporal filter to improve the depth data. We use noisy RGBD images from an inaccurate real-time depth sensor device in the whole process and later replace the color with data from a digital camera to generate realistic texture. Recently, several reconstruction approaches were presented acknowledging the potential of such real-time devices. However, those systems alone fail to retrieve small geometric characteristics from the object. The result of our experiments show a model with a considerable level of details, unexpected from low-quality RGBD images. We aim to use our pipeline to reconstruct objects with cultural value and add them to the virtual museum's database for visualization purpose.