Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Tadamasa Sawada

dblp:30/9838 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d reconstruction
0.212014
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
0.212014
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
0.212014
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
YearPublicationVenuePosition
2014 Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape Recovery
abstract
In 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. IEEE1