Demo Data from EDBT 2026 / reviewers in the wild / expert
Marvin Cheng
dblp:47/10484
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
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% | |
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 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
3d reconstruction |
0.1 | 1 | 2011 | Interactive 3D modeling of indoor environments with a consumer depth camera · UbiComp 2011 |
Computational photography and imaging › depth sensing
consumer depth camera |
0.1 | 1 | 2011 | Interactive 3D modeling of indoor environments with a consumer depth camera · UbiComp 2011 |
Interaction techniques and input › spatial interaction › 3d interaction
3d modeling interaction |
0.0 | 1 | 2011 | Interactive 3D modeling of indoor environments with a consumer depth camera · UbiComp 2011 |
Methods — techniques the papers use, named apart from their topics
depth sensing · 0.43d registration · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Interactive 3D modeling of indoor environments with a consumer depth cameraabstractDetailed 3D visual models of indoor spaces, from walls and floors to objects and their configurations, can provide extensive knowledge about the environments as well as rich contextual information of people living therein. Vision-based 3D modeling has only seen limited success in applications, as it faces many technical challenges that only a few experts understand, let alone solve. In this work we utilize (Kinect style) consumer depth cameras to enable non-expert users to scan their personal spaces into 3D models. We build a prototype mobile system for 3D modeling that runs in real-time on a laptop, assisting and interacting with the user on-the-fly. Color and depth are jointly used to achieve robust 3D registration. The system offers online feedback and hints, tolerates human errors and alignment failures, and helps to obtain complete scene coverage. We show that our prototype system can both scan large environments (50 meters across) and at the same time preserve fine details (centimeter accuracy). The capability of detailed 3D modeling leads to many promising applications such as accurate 3D localization, measuring dimensions, and interactive visualization. Hao Du 0004, Peter Henry, Xiaofeng Ren, Marvin Cheng, Dan B. Goldman, Steven M. Seitz, Dieter Fox |
UbiComp | 4 |