EDBT 2026 Demo / reviewers in the wild / expert
George Xu
dblp:164/8206
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 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 › range sensing
depth sensing |
0.2 | 1 | 2015 | Sensitivity study for object reconstruction using a network of time-of-flight depth sensors · ICRA 2015 |
Computer vision › 3D vision › 3d reconstruction
object reconstruction |
0.2 | 1 | 2015 | Sensitivity study for object reconstruction using a network of time-of-flight depth sensors · ICRA 2015 |
Computer vision › 3D vision › camera calibration
depth calibration |
0.1 | 1 | 2015 | Sensitivity study for object reconstruction using a network of time-of-flight depth sensors · ICRA 2015 |
Methods — techniques the papers use, named apart from their topics
time-of-flight sensing · 0.2sensor calibration · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Sensitivity study for object reconstruction using a network of time-of-flight depth sensorsabstractThis paper investigates the integration of multiple time-of-flight (ToF) depth sensors for object reconstruction. The advantage of such a sensor network is in the increased viewing coverage and addressing the problem of object self-occlusion. However, in utilizing a network of depth sensors, calibration and interference between the sensors can be one of the key challenges of their effective utilization. In comparison with infrared depth sensors, integration of time-of-flight sensors offer some new challenges. This paper presents experimental studies of practical factors that can affect such integration and proposes a guideline which can be used to avoid interferences. Using the proposed set-up, the paper also presents a method which can be used for reconstructing objects in such a sensor network. George Xu, Shahram Payandeh |
ICRA | 1 |