Active Image-based Modeling with a Toy Drone

TL;DR

This paper presents an automated system for image-based 3D modeling using a toy drone, which efficiently plans data capture views to improve model completeness and quality in real-time.

Contribution

It introduces a fast multi-view stereo algorithm combined with an online view planning method for autonomous data acquisition with a drone.

Findings

Improved efficiency in data collection for 3D modeling.

Ensured higher completeness of reconstructed models.

Validated system performance in simulated and real environments.

Abstract

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.