未来的手指和它的现代应用

Tanmay Sankhe, Pranav Puranik, Masira Mulla
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引用次数: 3

摘要

由智能可穿戴设备控制的手势调节系统引领了人机交互的下一个时代。手势具有直观和表现力,是一种更方便的交流方式。然而,为了开发一个手势控制系统,我们需要准确地检测指尖。在本文中,我们提出了一种可以被智能可穿戴设备有效利用的指尖检测系统。这种方法没有传统上用于检测指尖的标记和基于质心的技术。该系统的功能由框架中指尖的数量控制。我们整理了一个定制的数据集“1-2-3-4双手”,其中包含了使用一到四个手指做手势的不同手的图像。使用Faster RCNN和Inception v2模块,我们训练这个数据集来建立一个能够识别除拇指外的前四个指尖的模型。在实时手势控制系统中,指尖的计数用于执行操作。最后,我们实现了手指控制解决方案,如AirWriting, AirDrawing和游戏控制,并征集了他们的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Futuristic Finger and its Modern Day Applications
Gesture regulated systems controlled by smart wearables have spearheaded the next epoch in human machine interaction. Gestures being intuitive and expressive are a more convenient way of communication. However, for developing a gesture controlled system, we need to accurately detect fingertips. In this paper, we present a fingertip detection system that can be efficiently used by smart wearables. This approach is free of markers and centroid-based techniques which are traditionally used to detect fingertips.The system’s functionality is controlled by the number of fingertips in the frame. We collated a customized dataset, ‘1-2-3-4 Hands’, which contained the images of different hands gesturing using one to four fingers. Using Faster RCNN with Inception v2 module, we trained this dataset to build a model capable of recognizing any of the first four fingertips, excluding the thumb. The count of fingertips is used to perform an action in real-time gesture controlled systems. Finally, we have implemented finger-control solutions such as AirWriting, AirDrawing, and Gaming Controls and enlisted their benefits.
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