Art der Veröffentlichung: |
Artikel in Konferenzband |
Autor: |
Alexander Härtl, Ubbo Visser, Thomas Röfer |
Herausgeber: |
Sven Behnke, Manuela Veloso, Arnoud Visser, Rong Xiong |
Titel: |
Robust and Efficient Object Recognition for a Humanoid Soccer Robot |
Buch / Sammlungs-Titel: |
RoboCup 2013: Robot Soccer World Cup XVII |
Band: |
8371 |
Seite(n): |
396 – 407 |
Serie / Reihe: |
Lecture Notes in Artificial Intelligence |
Erscheinungsjahr: |
2014 |
Verleger: |
Springer, Heidelberg |
Abstract / Kurzbeschreibung: |
Static color classification as a first processing step of an object recognition system is still the de facto standard in the RoboCup Standard Platform League (SPL). Despite its efficiency, this approach lacks robustness with regard to changing illumination. We propose a new object recognition system where objects are found based on color similarities. Our experiments with line, goal, and ball recognition show that the new system is real-time capable on a contemporary NAO (version 3.2 and above). We show that the detection rate is comparable to color-table-based object recognition under static lighting conditions and substantially better under changing illumination. |
PDF Version: |
http://www.informatik.uni-bremen.de/kogrob/papers/RC-Haertl-etal-14.pdf |
Status: |
Reviewed |
Letzte Aktualisierung: |
10. 09. 2014 |