Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system

Abstract

This paper presents a new algorithm capable of improving the accuracy level of a laser pointer detector used within an interactive control device system. A genetic programming based approach has been employed to develop a focus of attention algorithm, which works cooperatively with a genetic fuzzy system. The idea is to improve the detection of laser-spots depicted on images captured by video cameras working on home environments. The new and more accurate detection system, in combination with an environment control system, allows to send correct orders to home devices. The algorithm is capable of eradicating false offs, thus preventing devices to autonomously activate/deactivate appliances when orders have not been really signalled by users. Moreover, by adding self-adjusting capabilities with a genetic fuzzy system the computer vision algorithm focuses its attention on a narrower area of the image. Extensive experimental results show that the combination of the focus of attention technique with dynamic thresholding and genetic fuzzy systems improves significantly the accuracy of the laser-spot detection system while maintaining extremely low false off rates in comparison with previous approaches.