摘要
Abstract
In view of the need for high-quality development,the human-computer interaction system needs to complete more dif-ficult,accurate and complex tasks.In the existing human-computer interaction system,the lack of gesture segmentation and recognition technology is the main reason that restricts the development of human-computer interaction system.Therefore,the improvement of gesture segmentation and recognition technology is the key factor to achieve an efficient and agile human-com-puter interaction system.To achieve higher quality gesture recognition,the improved convolutional neural network is used to segment and recognize gesture movements.The performance of the model is tested using gesture images in the database.The experimental results show that the accuracy of the gesture segmentation and recognition model based on convolution neural net-work is 99.07％,which has high accuracy and efficiency,improves the quality of gesture segmentation and recognition,and provides support for the improvement and application of human-computer interaction system.关键词
手势分割/手势识别/人机交互/深度学习/卷积神经网络Key words
gesture segmentation/gesture recognition/human-computer interaction/deep learning/convolutional neural net-work分类
信息技术与安全科学
