Hand gesture recognition via image processing techniques and deep CNN

计算机科学 卷积神经网络 人工智能 感兴趣区域 背景减法 计算机视觉 手势识别 手势 噪音(视频) 集合(抽象数据类型) 深度学习 模式识别(心理学) 图像(数学) 像素 程序设计语言
作者
Yao-Liang Chung,Hung‐Yuan Chung,Wei-Feng Tsai
出处
期刊:Journal of Intelligent and Fuzzy Systems [IOS Press]
卷期号:39 (3): 4405-4418 被引量:19
标识
DOI:10.3233/jifs-200385
摘要

In the present study, we sought to enable instant tracking of the hand region as a region of interest (ROI) within the image range of a webcam, while also identifying specific hand gestures to facilitate the control of home appliances in smart homes or issuing of commands to human-computer interaction fields. To accomplish this objective, we first applied skin color detection and noise processing to remove unnecessary background information from the captured image, before applying background subtraction for detection of the ROI. Then, to prevent background objects or noise from influencing the ROI, we utilized the kernelized correlation filters (KCF) algorithm to implement tracking of the detected ROI. Next, the size of the ROI image was resized to 100×120 and input into a deep convolutional neural network (CNN) to enable the identification of various hand gestures. In the present study, two deep CNN architectures modified from the AlexNet CNN and VGGNet CNN, respectively, were developed by substantially reducing the number of network parameters used and appropriately adjusting internal network configuration settings. Then, the tracking and recognition process described above was continuously repeated to achieve immediate effect, with the execution of the system continuing until the hand is removed from the camera range. The results indicated excellent performance by both of the proposed deep CNN architectures. In particular, the modified version of the VGGNet CNN achieved better performance with a recognition rate of 99.90% for the utilized training data set and a recognition rate of 95.61% for the utilized test data set, which indicate the good feasibility of the system for practical applications.
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