Demo Data from EDBT 2026 / reviewers in the wild / expert
Tomer Amiaz
dblp:41/3716
· DBLP profile ↗
4ranked-venue papers
3as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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 |
Image and video processing · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › texture analysis
dynamic texture analysis |
0.1 | 1 | 2009 | Dynamic Texture Detection Based on Motion Analysis · Int. J. Comput. Vis. 2009 |
Image and video processing › motion estimation
optical flow |
0.1 | 1 | 2006 | Piecewise-Smooth Dense Optical Flow via Level Sets · Int. J. Comput. Vis. 2006 |
Image and video processing
motion analysis |
0.0 | 1 | 2009 | Dynamic Texture Detection Based on Motion Analysis · Int. J. Comput. Vis. 2009 |
Image and video processing › mathematical imaging › partial differential equations for image processing
level set methods |
0.0 | 1 | 2006 | Piecewise-Smooth Dense Optical Flow via Level Sets · Int. J. Comput. Vis. 2006 |
Methods — techniques the papers use, named apart from their topics
spatiotemporal filtering · 0.1optical flow · 0.1level set · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Dynamic Texture Detection Based on Motion Analysis
Sándor Fazekas, Tomer Amiaz, Dmitry Chetverikov, Nahum Kiryati |
Int. J. Comput. Vis. | 2 |
| 2007 | Coarse to over-fine optical flow estimation
Tomer Amiaz, Eyal Lubetzky, Nahum Kiryati |
Pattern Recognit. | 1 |
| 2006 | Piecewise-Smooth Dense Optical Flow via Level Sets
Tomer Amiaz, Nahum Kiryati |
Int. J. Comput. Vis. | 1 |
| 2005 | Dense discontinuous optical flow via contour-based segmentationabstractWe propose a new algorithm for dense optical flow computation. Dense optical flow schemes are challenged by the presence of motion discontinuities. In state of the art optical flow methods, over-smoothing of flow discontinuities accounts for most of the error. A breakthrough in the performance of optical flow computation has recently been achieved by Brox et al. Our algorithm embeds their functional within a contour-based segmentation framework. Piecewise-smooth flow fields are accommodated and flow boundaries are crisp. Experimental results show the superiority of our algorithm with respect to alternative techniques. Tomer Amiaz, Nahum Kiryati |
ICIP (3) | 1 |