Mobile robot control using hand-shape recognition

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 an image obtained from a moving camera. For this, we use an active contour model-based tracking approach with mean shift, which reduces the dependency of the active contour model on the location of the initial curve. The proposed system consists of four modules: a hand detector, a hand tracker, a hand-shape recognizer and a robot controller. The hand detector detects a skin-colour region, which has a specific shape, as a hand in an image. Then, hand tracking is performed using an active contour model with mean shift. Thereafter, hand-shape recognition is performed using Hu moments. To assess the validity of the proposed system, we tested the proposed system on a walking robot, KHR-1. The experimental results show the effectiveness of the proposed system.