Abstract
Accurate world modeling is important for efficient multi-robot planning in robot soccer. Visual detection of the robots on the field in addition to all other objects of interest is crucial to achieve this goal. The problem of robot detection gets even harder when robots with only on board sensing capabilities, limited field of view, and restricted processing power are used. This work extends the real-time object detection framework proposed by Viola and Jones, and utilizes the unique chest and head patterns of Nao humanoid robots to detect them in the image. Experiments demonstrate rapid detection with an acceptably low false positive rate, which makes the method applicable for real-time use.
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References
The RoboCup Standard Platform League, http://www.tzi.de/spl
Aldebaran-Nao, http://www.aldebaran-robotics.com/eng/Nao.php
Fasola, J., Veloso, M.: Real-Time Object Detection using Segmented and Grayscale Images. In: Proceedings of ICRA 2006, May 2006, pp. 4088–4093 (2006)
The Sony Aibo robots, http://support.sony-europe.com/aibo/
Viola, P., Jones, M.: Rapid Object Detection using a Boosted Cascade of Simple Features. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, p. 511. IEEE Computer Society, Los Alamitos (2001)
Viola, P.A., Jones, M.J.: Robust Real-Time Face Detection. International Journal of Computer Vision 57(2), 137–154 (2004)
Seo, N.: Tutorial: OpenCV haartraining (Rapid Object Detection With A Cascade of Boosted Classifiers Based on Haar-Like Features) (2007)
Bradski, G.: The OpenCV Library. Dr. Dobb’s Journal of Software Tools (2000)
Papageorgiou, C.P., Oren, M., Poggio, T.: A general framework for object detection. In: ICCV 1998: Proceedings of the Sixth International Conference on Computer Vision, Washington, DC, USA, p. 555. IEEE Computer Society, Los Alamitos (1998)
Webots Mobile Robot Simulation Environment, http://www.cyberbotics.com
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© 2011 Springer-Verlag Berlin Heidelberg
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Daniş, F.S., Meriçli, T., Meriçli, Ç., Akın, H.L. (2011). Robot Detection with a Cascade of Boosted Classifiers Based on Haar-Like Features. In: Ruiz-del-Solar, J., Chown, E., Plöger, P.G. (eds) RoboCup 2010: Robot Soccer World Cup XIV. RoboCup 2010. Lecture Notes in Computer Science(), vol 6556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20217-9_35
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DOI: https://doi.org/10.1007/978-3-642-20217-9_35
Publisher Name: Springer, Berlin, Heidelberg
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