Name
Abstract | ||
|---|---|---|
This paper proposes a method to analyse human-made environments regarding the existence of descending stairs and steps to assists visually impaired and furthermore disabled people, that are not able to use traditional supports like blind canes. Those people are heavily limited in their daily lives, since wrong decisions caused by the lack of information can easily lead to accidents. We use depth data acquired with a low-resolution Time-of-Flight (ToF) camera to perceive the scene in front a mobile vehicle (rollator) to provide the user with detailed information about potentially hazardous situations. Experiments with affected persons have shown the ability of the system to help them understand the environment and, in particular, avoid falls from descending stairs. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/IVS.2015.7225712 | 2015 IEEE Intelligent Vehicles Symposium (IV) |
Keywords | Field | DocType |
descending step classification,time-of-flight sensor data,visually impaired people,disabled people,low-resolution ToF camera,time-of-flight camera | Computer vision,Mobile vehicle,Artificial intelligence,Engineering,Time of flight sensor,Stairs | Conference |
ISSN | Citations | PageRank |
1931-0587 | 1 | 0.37 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carsten Stahlschmidt | 1 | 1 | 1.04 |
| Sebastian von Camen | 2 | 1 | 0.37 |
| Alexandros Gavriilidis | 3 | 3 | 1.42 |
| Anton Kummert | 4 | 234 | 55.14 |