Demo Data from SIGIR 2026 / reviewers in the wild / expert
H.-F. Cheung
dblp:46/2523
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 2
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% | |
| Computer graphics and multimedia
1 paper |
Computational photography and imaging · 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 › range sensing
depth sensing |
0.0 | 1 | 1995 | Improving Laser Triangulation Sensors Using Polarization · ICCV 1995 |
Computer vision › 3D vision › range sensing
laser triangulation |
0.0 | 1 | 1995 | Improving Laser Triangulation Sensors Using Polarization · ICCV 1995 |
Computational photography and imaging
polarization imaging |
0.0 | 1 | 1995 | Improving Laser Triangulation Sensors Using Polarization · ICCV 1995 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Using Light Polarization in Laser ScanningabstractWe use polarization analysis in triangulation-based laser scanners to disambiguate the true laser stripe from spurious inter-reflections caused by holes and concavities on metal surfaces. Stripe candidates are discriminated by projecting linearly polarised laser light and measuring the polarization state of the linearly polarized component of the observed stripe candidates. Initial experimental results are reported and discussed. James Clark 0001, Emanuele Trucco, H.-F. Cheung |
BMVC | 3 |
| 1995 | Improving Laser Triangulation Sensors Using PolarizationabstractWe report a novel application of polarization based vision addressing the robustness of laser triangulation range sensors. Such sensors are based on the accurate detection of a pattern of laser light projected onto a scene, usually a point or line. Typical problems arise with highly specularly reflective surfaces, which can generate visible reflections of the light in various parts of the image. This can confuse the detection algorithms and lead to wrong range measurements. This paper demonstrates experimentally the feasibility of polarization based vision for disambiguating multiple specular inter reflections of the laser light. We concentrate on metal components as they have high interest for inspection in manufacturing, and show positive results with situations of various complexities.> James Clark 0001, Emanuele Trucco, H.-F. Cheung |
ICCV | 3 |