Computer Graphics
TU Braunschweig

Multi-Image Correspondences

Abstract

Multi-view video camera setups record many images that capture nearly the same scene at nearly the same instant in time. Neighboring images in a multi-video setup restrict the solution space between two images: correspondences between one pair of images must be in accordance with the correspondences to the neighboring images.

The concept of accordance or consistency for correspondences between three neighboring images can be employed in the estimation of dense optical flow and in the matching of sparse features between three images.

This work has been funded in parts by the ERC Grant #256941 `Reality CG` and the German Science Foundation, DFG MA2555/4-2.


Code and Resources

The code and the test sequences are for research purposes only. No commercial usage is allowed in any form. If you use this code for your publications, make sure to cite the corresponding papers. Start downloading the test sequences by clicking on the images.

Publications

Christian Lipski, Felix Klose, Marcus Magnor:
Correspondence and Depth-Image Based Rendering: a Hybrid Approach for Free-Viewpoint Video
in IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), vol. 24, no. 6, pp. 942-951, June 2014.

Thomas Neumann, Kiran Varanasi, Nils Hasler, Markus Wacker, Marcus Magnor, Christian Theobalt:
Capture and Statistical Modeling of Arm-Muscle Deformations
in Computer Graphics Forum (Proc. of Eurographics EG), vol. 32, no. 2, pp. 285-294, May 2013.

Anita Sellent:
Dense Correspondence Field Estimation from Multiple Images
PhD thesis, TU Braunschweig, June 2011.
Monsenstein und Vannerdat, ISBN 978-3-86991-339-1



Anita Sellent, Christian Linz, Marcus Magnor:
Consistent Optical Flow for Stereo Video
in Proc. IEEE International Conference on Image Processing (ICIP), pp. 1-4, September 2010.

Related Projects

Alternate Exposure Imaging

Traditional optic flow algorithms rely on consecutive short-exposure images. In contrast, long-exposed images contain integrated motion information directly in form of motion blur. In this project, we use the additional information provided by a long exposure image to improve robustness and accuracy of motion field estimation. Furthermore, the long exposure image can be used to determine the moment of occlusion for the pixels in any of the short exposure images that are occluded or disoccluded.

This work has been funded by the German Science Foundation, DFG MA2555/4-1

Image-space Editing of 3D Content

The goal of this project is to develop algorithms in image space that allow photo-realistic editing of dynamic 3D scenes. Traditional 2D editing tools cannot be applied to 3D video as in addition to correspondences in time spatial correspondences are needed for consistent editing. In this project we analyze how to make use of the redundancy in multi-stereoscopic videos to compute robust and dense correspondence fields. these space-time correspondences can then be used to propagate changes applied to one frame consistently to all other frames in the video. Beside the transition of classical video editing tools we want to develop new tools specifically for 3D video content.

This project has been funded by ERC Grant #256941 `Reality CG` and the German Science Foundation, DFG MA2555/4-2.

Perception-motivated Interpolation of Image Sequences

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