Active Image-based Modeling with a Toy Drone

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.

Video Demo

On Youku (In China)

On Youtube

Publication

[1] Rui Huang, Danping Zou, Richard Vaughan and Ping Tan, Active Image-based Modeling with a Toy Drone, International Conference on Robotics and Automation, Brisbane, Australia, May 2018. PDF

Contact

Please feel free to contact me if you are interested in this work.

Rui Huang, Alibaba AI Labs

Email: huangrui815@gmail.com

Personal Webpage: http://www.sfu.ca/~rha55/