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


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 } }