Frankenhorse: Automatic Completion of Articulating Objects from Image-based Reconstruction
In Proceedings British Machine Vision Conference 2014
http://dx.doi.org/10.5244/C.28.106
Abstract
Structure from Motion reconstructions of objects often contain holes. While small holes can be completed with a smoothness prior, completing large holes requires a higher-level understanding of the object. We present a method to complete large holes in articulating objects by reconstructing and aligning sets of objects of the same class, using the well-reconstructed parts in each model to complete holes in the others, resulting in a `Frankenhorse' completion. Our proposed method is fully automatic, yet is able to handle articulation, intra-class variation, holes and clutter present in the reconstructions. This is achieved through our novel segmentation and clutter removal processes as well as by the use of a robust method for piecewise-rigid registration of the models. We show that our method can fill large holes even when only a small set of models with high variability and low reconstruction quality is available.
Session
Poster Session
Files
Extended Abstract (PDF, 1 page, 3.8M)Paper (PDF, 12 pages, 8.6M)
Supplemental Materials (ZIP, 9.4M)
Bibtex File
Citation
Alex Mansfield, Nikolay Kobyshev, Hayko Riemenschneider, Will Chang, and Luc Van Gool. Frankenhorse: Automatic Completion of Articulating Objects from Image-based Reconstruction. Proceedings of the British Machine Vision Conference. BMVA Press, September 2014.
BibTex
@inproceedings{BMVC.28.106
title = {Frankenhorse: Automatic Completion of Articulating Objects from Image-based Reconstruction},
author = {Mansfield, Alex and Kobyshev, Nikolay and Riemenschneider, Hayko and Chang, Will and Van Gool, Luc},
year = {2014},
booktitle = {Proceedings of the British Machine Vision Conference},
publisher = {BMVA Press},
editors = {Valstar, Michel and French, Andrew and Pridmore, Tony}
doi = { http://dx.doi.org/10.5244/C.28.106 }
}