VLDB 2026 Research / reviewers in the wild / expert
Tadamasa Sawada
dblp:30/9838
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2014
0000-0002-7167-1464ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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% | |
| Theoretical computer science
1 paper |
Computational geometry · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
3d reconstruction |
0.2 | 1 | 2014 | Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape Recovery · Proc. IEEE 2014 |
Computer vision › 3D vision
3d shape reconstruction |
0.2 | 1 | 2014 | Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape Recovery · Proc. IEEE 2014 |
Computer vision › 3D vision › 3d reconstruction › geometric reconstruction
symmetry-based reconstruction |
0.2 | 1 | 2014 | Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape Recovery · Proc. IEEE 2014 |
Methods — techniques the papers use, named apart from their topics
perspective projection · 0.4orthographic projection · 0.4a priori constraints · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape RecoveryabstractIn this paper, we take up the long-standing problem of how to recover 3-D shapes represented by a 2-D image, such as the image on the retina of the eye, or in a video camera. Our approach is biologically grounded in a theory of how the human visual system solves this problem, focusing on shapes that are mirror symmetrical in 3-D. A 3-D mirror-symmetrical shape can be recovered from a single 2-D orthographic or perspective image by applying several a priori constraints: 3-D mirror symmetry, 3-D compactness, and planarity of contours. From the computational point of view, the application of a 3-D symmetry constraint is challenging because it requires establishing 3-D symmetry correspondence among features of a 2-D image, which itself is asymmetrical for almost all viewing directions relative to the 3-D symmetrical shape. We describe new invariants of a 3-D to 2-D projection for the case of a pair of mirror-symmetrical planar contours, and we formally state and prove the necessary and sufficient conditions for detection of this type of symmetry in a single orthographic and perspective image. Tadamasa Sawada, Zygmunt Pizlo |
Proc. IEEE | 1 |