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Hardware application of human-machine interface in smart air conditioners using hand tracking

机译:人机界面在智能空调中手动跟踪的硬件应用

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The aim of this paper is to present a real time application for air condition systems using hand recognition and tracking. The hardware requirements of the system, limited by only a simple USB webcam and a Beagle Board, which is a compact and low cost hardware. Our approach uses a simple motion detection trying to eliminate unnecessary regions of the image and a recognition algorithm based on Haar classifiers. An intelligent method and a practical application for detecting four hand movement instructions have been proposed for air condition systems in smart homes using Beagle Board. The system translates the detected gestures into different functional inputs and interfaces to air conditioner. The proposed method is also intelligent because it has an optimized multi layered neural network which is also optimized by a swarm-intelligence-based global optimization algorithm, Artificial Bee Colony Algorithm.
机译:本文的目的是提出一种使用手识别和跟踪的空调系统实时应用程序。系统的硬件要求仅受简单的USB网络摄像头和Beagle Board的限制,后者是一种紧凑且低成本的硬件。我们的方法使用简单的运动检测来尝试消除图像的不必要区域,并使用基于Haar分类器的识别算法。提出了一种利用比格尔板在智能家居空调系统中检测四种手部动作指令的智能方法和实际应用。该系统将检测到的手势转换为不同的功能输入和空调接口。所提出的方法也是智能的,因为它具有优化的多层神经网络,该网络也通过基于群体智能的全局优化算法(人工蜂群算法)进行了优化。

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