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Remote control with accelerometer-based hand gesture recognition for interaction in digital TV

机译:通过基于加速度计的手势识别进行远程控制,实现数字电视中的交互

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At the present, the digital TV allows the access to a greater amount of content and to execute interactive applications. The remote control used to control the digital TV systems is, in most cases, still solved by the traditional infrared remote control, which has become a limiting factor on the user interaction with the TV. This paper introduces the design and development of an interaction device for use in the context of digital TV in Argentina. The proposed device can be considered an evolution of the classic remote control, in which the functionality of hand gesture recognition is implemented as a natural and friendly interface for controlling digital TV systems of the home. A gestural dictionary of 20 types of gestures was adopted. The recognized gestures are translated into control commands for digital TV systems. As the hand gesture recognition is a pattern classification problem, two techniques based on artificial neural networks were explored, in order to compare results and to select the tool that best fits the problem in question. The pattern classifier design was described in detail, in order to properly select the hardware platform, fulfilling requirements of low-cost and fast execution of pattern classification algorithms. An interaction device of low-cost and excellent recognition precision was developed, for enhancing and enriching the user experience.
机译:目前,数字电视允许访问更大量的内容并执行交互式应用程序。在大多数情况下,用于控制数字电视系统的遥控器仍由传统的红外遥控器解决,这已成为限制用户与电视互动的因素。本文介绍了在阿根廷数字电视环境中使用的交互设备的设计和开发。所提出的设备可以被认为是经典遥控器的演进,其中手势识别的功能被实现为用于控制家庭数字电视系统的自然友好的界面。使用了20种手势的手势字典。识别出的手势被转换为数字电视系统的控制命令。由于手势识别是一种模式分类问题,因此探索了两种基于人工神经网络的技术,以便比较结果并选择最适合所讨论问题的工具。详细描述了模式分类器的设计,以正确选择硬件平台,满足低成本和快速执行模式分类算法的要求。开发了一种低成本和出色识别精度的交互设备,以增强和丰富用户体验。

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