Demo Data from EDBT 2026 / reviewers in the wild / expert
Kai Ruhl
dblp:18/10490
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorArtificial intelligence and machine learning · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
2 papers |
Rendering · 54% Image and video processing · 39% Virtual and augmented reality · 7% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering
image-based rendering |
0.4 | 2 | 2015 | Interactive Scene Flow Editing for Improved Image-based Rendering and Virtual Spacetime Navigation · ACM Multimedia 2015 Improving dense image correspondence estimation with interactive user guidance · ACM Multimedia 2012 |
Image and video processing › motion analysis
scene flow estimation |
0.2 | 1 | 2015 | Interactive Scene Flow Editing for Improved Image-based Rendering and Virtual Spacetime Navigation · ACM Multimedia 2015 |
Image and video processing › image matching
dense correspondence estimation |
0.1 | 1 | 2012 | Improving dense image correspondence estimation with interactive user guidance · ACM Multimedia 2012 |
Rendering › image-based rendering
view interpolation |
0.1 | 1 | 2012 | Improving dense image correspondence estimation with interactive user guidance · ACM Multimedia 2012 |
Methods — techniques the papers use, named apart from their topics
optimization · 0.2interactive editing · 0.2subpixel precision · 0.1multi-level user guidance · 0.1interactive correspondence display · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Interactive Scene Flow Editing for Improved Image-based Rendering and Virtual Spacetime NavigationabstractHigh-quality stereo and optical flow maps are essential for a multitude of tasks in visual media production, e.g. virtual camera navigation, disparity adaptation or scene editing. Rather than estimating stereo and optical flow separately, scene flow is a valid alternative since it combines both spatial and temporal information and recently surpassed the former two in terms of accuracy. However, since automated scene flow estimation is non-accurate in a number of situations, resulting rendering artifacts have to be corrected manually in each output frame, an elaborate and time-consuming task. We propose a novel workflow to edit the scene flow itself, catching the problem at its source and yielding a more flexible instrument for further processing. By integrating user edits in early stages of the optimization, we allow the use of approximate scribbles instead of accurate editing, thereby reducing interaction times. Our results show that editing the scene flow improves the quality of visual results considerably while requiring vastly less editing effort. Kai Ruhl, Martin Eisemann, Anna Hilsmann, Peter Eisert, Marcus A. Magnor |
ACM Multimedia | 1 |
| 2012 | Improving dense image correspondence estimation with interactive user guidanceabstractHigh quality dense image correspondence estimation between two images is an essential pre-requisite for view interpolation in visual media production. Due to the ill-posed nature of the problem, automated estimation approaches are prone to erroneous correspondences and subsequent quality degradation, e.g. in the presence of ambiguous movements that require human scene understanding to resolve. Where visually convincing results are essential, artifacts resulting from estimation errors must be repaired by hand with image editing tools. In this paper, we propose a new workflow alternative by fixing the correspondences instead of fixing the interpolated images. We combine realtime interactive correspondence display, multi-level user guidance and algorithmic subpixel precision to counteract failure cases of automated estimation algorithms. Our results show that already few interactions improve the visual quality considerably. Kai Ruhl, Benjamin Hell, Felix Klose, Christian Lipski, Sören Petersen, Marcus A. Magnor |
ACM Multimedia | 1 |
| 2012 | A loop-consistency measure for dense correspondences in multi-view video
Anita Sellent, Kai Ruhl, Marcus A. Magnor |
Image Vis. Comput. | 2 |