3-D modeling Using a Monocular Plenoptic Camera
A plenoptic camera is a passive, off-the-shelf industrial camera that has been reengineered to measure the focused depth of image projections within the camera. Using this information and with the help of a calibrated camera model, it is possible to infer the depth of the scene in front of the camera. Contrary to widespread depth cameras like the Kinect or time-of-flight cameras, plenoptic cameras only require one lens aperture and they do not need to actively emit any radiation unto the environment.
Recently we published a method to metrically calibrate a plenoptic camera in a previously unattained level of accuracy. We now have the opportunity to be the first to model an object in 3-D using a single plenoptic camera in an accurate, metric way. To that end, synthetic brightness images and metric depth images are available. For instance, the brightness images can be used for up-to-scale 3-D modeling, using bundle adjustment and dense structure from motion (e.g. using our institute's SGM implementation). After that, the metric depth images can be used to optimally apply the correct metric scale to the reconstructed model.
Degree courses in engineering, computer science, maths or related with above-average grades
Good coding skills in C++, Python, and Matlab
Preferable: prior experience in computer graphics
A. Lumsdaine, T. G. Georgiev. "The Focused Plenoptic Camera." In: Proceedings of the International Conference on Computational Photography (ICCP), 2009.
K. H. Strobl and M. Lingenauber. "Stepwise Calibration of Focused Plenoptic Cameras." Computer Vision and Image Understanding (CVIU), Volume 145, April 2016, pp. 140-147.
F. Dellaert, S. Seitz, C. Thorpe, and S. Thrun. "Structure from Motion without Correspondence." IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2000.
Noah Snavely, Steven M. Seitz, and Richard Szeliski. "Modeling the World from Internet Photo Collections." International Journal of Computer Vision, 2007.
Heiko Hirschmueller, "Stereo Processing by Semi-Global Matching and Mutual Information." in IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 30(2), February 2008, pp. 328-341.