Active Image-based Modeling with a Toy Drone
This addresses the tedious and time-consuming manual image capture process for users of image-based modeling, though it is incremental as it builds on existing techniques.
The paper tackled the problem of automating data capturing for image-based 3D modeling by developing a system that uses a fast multi-view stereo algorithm and next-best-view planning with a toy drone, improving efficiency and ensuring model completeness in simulated, indoor, and outdoor experiments.
Image-based modeling techniques can now generate photo-realistic 3D models from images. But it is up to users to provide high quality images with good coverage and view overlap, which makes the data capturing process tedious and time consuming. We seek to automate data capturing for image-based modeling. The core of our system is an iterative linear method to solve the multi-view stereo (MVS) problem quickly and plan the Next-Best-View (NBV) effectively. Our fast MVS algorithm enables online model reconstruction and quality assessment to determine the NBVs on the fly. We test our system with a toy unmanned aerial vehicle (UAV) in simulated, indoor and outdoor experiments. Results show that our system improves the efficiency of data acquisition and ensures the completeness of the final model.