A Visual Human-Computer Interaction System Based on Hybrid Visual Model

نویسندگان

چکیده

The traditional human-computer interaction is mainly through the mouse, keyboard, remote control, and other peripheral equipment electromagnetic signal transmission. This paper aims to build a visual system series of deep learning machine vision models, so that people can achieve complete only camera screen. established includes function modes three basic peripherals in interaction: mouse (X-Y position indicator), control. convex hull method was used switch between these modes. After issuing mode command, Gaussian mixture quickly identify moving human body narrow scope our image processing. Subsequently, finger detection realized based on Faster-RCNN-ResNET50-FPN model structure, keyboard relationship different fingers. At same time, recognition posture done by using MediaPipe BlazePose, action classification models were Angle movements as realize control In order ensure real-time performance interactive system, according characteristics data processing processes, CPU GPU computing power resources are cross-process images performance. accuracy above 0.9 for key feature points body, 0.87 four kinds command actions. It hoped vision-based will become widely future.

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ژورنال

عنوان ژورنال: Security and Communication Networks

سال: 2022

ISSN: ['1939-0122', '1939-0114']

DOI: https://doi.org/10.1155/2022/9562104