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ROBOCUP
2007
Springer

Detection of AIBO and Humanoid Robots Using Cascades of Boosted Classifiers

10 years 5 months ago
Detection of AIBO and Humanoid Robots Using Cascades of Boosted Classifiers
Abstract. In the present article a framework for the robust detection of mobile robots using nested cascades of boosted classifiers is proposed. The boosted classifiers are trained using Adaboost and domain-partitioning weak hypothesis. The most interesting aspect of this framework is its capability of building robot detection systems with high accuracy in dynamical environments (RoboCup scenario), which achieve, at the same time, high processing and training speed. Using the proposed framework we have built robust AIBO and humanoid robot detectors, which are analyzed and evaluated using real-world video sequences.
Matías Arenas, Javier Ruiz-del-Solar, Rodri
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where ROBOCUP
Authors Matías Arenas, Javier Ruiz-del-Solar, Rodrigo Verschae
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