文章基本信息

标题：Effective Computer Vision Techniques for RealTime Hand Gesture Recognition and Detection
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作者：Jayshree Pansare ; Gajanan Aochar ; Tejashree Salvi 等
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2021
卷号：3
期号：5
页码：13-18
DOI：10.35629/5252-0304521523
语种：English
出版社：IJAEM JOURNAL
摘要：Gesture recognition technique is changing our relationship with technical devices by providing contactless or touchless user interface and opening the door to a whole new world of input possibilities. The main purpose of this paper is to explore the different gesture recognition and detection techniques. This paper describes research of gesture recognition and detection techniques that uses the knowledge of existing machine learning, deep learning, image processing and motion detection techniques. This also helps to advance the existing applications that a normal operating system provides by allowing users to interact with its applications with hand gestures which could be of their choice. After analyzing the research background for gesture control applications, we obtain that not all gesture control applications are cross-platform applications and lacking the high precision gesture recognition and detection techniques. The dataset would contain static and dynamic gestures. The important and reasonable „Cross-platform' feature makes the operating system suitable to operate multiple portable devices such as routers, TV, mobile phones, Laptop/Desktop, Refrigerators etc. with hand gestures. Gesture based operating system could help people in different aspects and can be used in different fields such as healthcare, entertainment(gaming) and helps physically challenged people to enter into the world of technology.
关键词：Hand Gesture Recognition;Operating System;Machine Learning;Deep Learning;Image Processing;CNN;SVM;YOLOv3;OpenCV;cross-platform;static gestures;dynamic gestures