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Mobile Robot Control using Hand Shape Recognition

Young-Rae Kim, Eun Yi Kim, Jae-Sik Chang, Sehyun Park

Year
2008
Citations
2

Abstract

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

Keywords

Artificial intelligenceComputer visionComputer scienceTracking (education)Controller (irrigation)RobotDetectorMobile robotTracking systemKalman filter

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