NAO Robot Player Recognition Based on Haar-like Features and Color Features

doi:10.3969/j.issn.1006-2475.2017.02.006

Abstract

Abstract:

In the RoboCup games, recognition of the players is the basis of route planning, passing and other top strategy. Due to the limitation of hardware condition of NAO robot and the disturber of the background, the speed and accuracy of the algorithm are required. In order to meet these requirements, a recognition algorithm based on Haar-like features and cascade Adaboost classifier is proposed. Firstly, NAO was first recognized by a cascade classifier trained by the Adaboost algorithm in the offline environment; then, the candidate target regions are identified by using the color histogram matching for second times, in the removal of false detection area at the same time, NAO also identified other robots being friend or foe. The experimental results show that this method can effectively identify the NAO robot, and meet the requirements of the robustness and real-time of the recognition algorithm.
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Key words: NAO robot, Haar-like feature, cascade classifier, color histogram matching

CLC Number:

TP391.4

ZHANG Jun-jie1, DING Shu-yan2, LI Lun-bo1. NAO Robot Player Recognition Based on Haar-like Features and Color Features[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.02.006.

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