Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael Hatzitheodorou
dblp:40/6650
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1998
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory of computation · 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.
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
shape from shading |
0.0 | 1 | 1988 | An optimal algorithm for the derivation of shape from shadows · CVPR 1988 |
Computer vision › 3D vision › 3d shape reconstruction › shape from x
shape from shadow |
0.0 | 1 | 1988 | An optimal algorithm for the derivation of shape from shadows · CVPR 1988 |
Computer vision › 3D vision › 3d reconstruction
surface reconstruction |
0.0 | 1 | 1988 | An optimal algorithm for the derivation of shape from shadows · CVPR 1988 |
Methods — techniques the papers use, named apart from their topics
spine algorithm · 0.0parallel computation · 0.0hilbert space formulation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1998 | Shape from Shadows: A Hilbert Space Setting
Michael Hatzitheodorou |
J. Complex. | 1 |
| 1988 | An optimal algorithm for the derivation of shape from shadowsabstractThe authors study the problem of recovering a surface slice from the shadows it casts on itself when lighted by the sun at various times of the day. The problem is formulated and solved in a Hilbert space setting. The spine algorithm interpolating the data that result from the shadows is constructed. This algorithm is optimal in terms of the approximation error and has low cost. The authors implement the optimal error algorithm and show a series of test runs. Another modified version of the algorithm that improves the cost considerably is also shown. This version is suited for parallel computation with further reductions in the cost of the solution.> Michael Hatzitheodorou, John R. Kender |
CVPR | 1 |