Fast Image Segmentation, Object Recognition and Localization in a RoboCup Scenario (bibtex)
by T Bandlow, M Klupsch, R Hanek and T Schmitt
Abstract:
This paper presents the vision system of the robot soccer team Agilo RoboCuppers the RoboCup team of the image understanding group (FG BV) at the Technische Universität München. The name is derived from the Agilolfinger, which were the first Bavarian ruling dynasty in the 8th century, with Tassilo as its most famous representative. We present a fast and robust color classification method yielding significant regions in the image. The boundaries between adjacent regions are used to localize objects like the ball or other robots on the field. Furthermore for each player the free motion space is determined and its position and orientation on the field is estimated. All this is done completely vision based, without any additional sensors.
Reference:
Fast Image Segmentation, Object Recognition and Localization in a RoboCup Scenario (T Bandlow, M Klupsch, R Hanek and T Schmitt), In 3. RoboCup Workshop, IJCAI 99, 1999.
Bibtex Entry:
@inproceedings{bandlow_fast_1999, author = {T Bandlow and M Klupsch and R Hanek and T Schmitt}, title = {Fast Image Segmentation, Object Recognition and Localization in a {RoboCup} Scenario}, booktitle = {3. {RoboCup} Workshop, {IJCAI} 99}, year = {1999}, pages = {174–185}, abstract = {This paper presents the vision system of the robot soccer team Agilo {RoboCuppers} the {RoboCup} team of the image understanding group ({FG} {BV)} at the Technische Universität München. The name is derived from the Agilolfinger, which were the first Bavarian ruling dynasty in the 8th century, with Tassilo as its most famous representative. We present a fast and robust color classification method yielding significant regions in the image. The boundaries between adjacent regions are used to localize objects like the ball or other robots on the field. Furthermore for each player the free motion space is determined and its position and orientation on the field is estimated. All this is done completely vision based, without any additional sensors.}, }
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