Abstract
We present a novel variational approach to estimate dense depth maps from multiple images in real-time. By using robust penalizers for both data term and regularizer, our method preserves discontinuities in the depth map. We demonstrate that the integration of multiple images substantially increases the robustness of estimated depth maps to noise in the input images. The integration of our method into recently published algorithms for camera tracking allows dense geometry reconstruction in real-time using a single handheld camera. We demonstrate the performance of our algorithm with real-world data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jin, H., Favaro, P., Soatto, S.: Real-time 3-d motion and structure of point-features: A front-end for vision-based control and interaction. In: Int. Conf. on Computer Vision and Pattern Recognition, pp. 2778–2779 (2000)
Nister, D.: Preemptive ransac for live structure and motion estimation. In: IEEE Int. Conf. on Computer Vision, pp. 199–206 (2003)
Kolev, K., Cremers, D.: Continuous ratio optimization via convex relaxation with applications to multiview 3d reconstruction. In: CVPR, pp. 1858–1864. IEEE, Los Alamitos (2009)
Zach, C., Pock, T., Bischof, H.: A globally optimal algorithm for robust TV-L1 range image integration. In: IEEE Int. Conf. on Computer Vision, Rio de Janeiro, Brazil. LNCS. IEEE, Los Alamitos (2007)
Pock, T., Schoenemann, T., Graber, G., Bischof, H., Cremers, D.: A convex formulation of continuous multi-label problems. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 792–805. Springer, Heidelberg (2008)
Slesareva, N., Bruhn, A., Weickert, J.: Optic flow goes stereo: A variational method for estimating discontinuity-preserving dense disparity maps. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds.) DAGM 2005. LNCS, vol. 3663, pp. 33–40. Springer, Heidelberg (2005)
Zach, C., Pock, T., Bischof, H.: A duality based approach for realtime TV-L1 optical flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 214–223. Springer, Heidelberg (2007)
Newcombe, R.A., Davison, A.J.: Live dense reconstruction with a single moving camera. In: Int. Conf. on Computer Vision and Pattern Recognition (2010)
Chambolle, A.: An algorithm for total variation minimization and applications. J. Math. Imaging Vis. 20(1-2), 89–97 (2004)
Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Phys. D 60(1-4), 259–268 (1992)
Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: Proc. Sixth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2007), Nara, Japan (November 2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stühmer, J., Gumhold, S., Cremers, D. (2010). Real-Time Dense Geometry from a Handheld Camera. In: Goesele, M., Roth, S., Kuijper, A., Schiele, B., Schindler, K. (eds) Pattern Recognition. DAGM 2010. Lecture Notes in Computer Science, vol 6376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15986-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-15986-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15985-5
Online ISBN: 978-3-642-15986-2
eBook Packages: Computer ScienceComputer Science (R0)