EDBT 2026 Demo / reviewers in the wild / expert
Tinosch Ganjineh
dblp:41/9943
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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 |
Autonomous driving · 77% Face, body and person analysis · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Autonomous driving
driver assistance |
0.2 | 1 | 2016 | Traffic awareness driver assistance based on stereovision, eye-tracking, and head-up display · ICRA 2016 |
Methods — techniques the papers use, named apart from their topics
stereo vision · 0.2head-up display · 0.2fiducial markers · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Traffic awareness driver assistance based on stereovision, eye-tracking, and head-up displayabstractThis paper presents a system which constantly monitors the level of attention of a driver in traffic. The vehicle is instrumented and can identify the state of traffic-lights, as well as obstacles on the road. If the driver is inattentive and fails to recognize a threat, the assistance system produces a warning. Therefore, the system helps the driver to focus on crucial traffic situations. Our system consists of three components: computer vision detection of traffic-lights and other traffic participants, an eye tracking device used also for head localization, and finally, a human machine interface consisting of a head-up display and an acoustic module used to provide warnings to the driver. The orientation of the driver's head is detected using fiducial markers visible in video frames. We describe how the system was integrated using an autonomous car as experimental ADAS platform. Tobias Langner 0002, Daniel Seifert, Bennet Fischer, Daniel Göhring, Tinosch Ganjineh, Raúl Rojas 0001 |
ICRA | 5 |