Fast Color-Independent Ball Detection for Mobile Robots

Abstract

This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge filtered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classification and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classification is real-time capable and reliable.