https://scholars.lib.ntu.edu.tw/handle/123456789/640007
標題: | Real-Time Hand Gesture Recognition Using Depth Information and Path Analysis | 作者: | Wu, You Jia JIAN-JIUN DING |
關鍵字: | depth sensor | dynamic hand gesture recognition | moving object detection | moving trace analysis | video processing | 公開日期: | 1-一月-2023 | 來源出版物: | 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering, ECICE 2023 | 摘要: | Applications of human-computer interaction (HCI) have become common recently. Among a variety of methods, hand gestures are used in communication natural tools. Thus, hand gesture recognition has been popular in research, especially the vision-based methods with the advantage of contact-free characteristics. In this study, we developed a real-time vision-based dynamic hand gesture recognition system to continuously classify 6 different gestures: 4 directions of swipe and 2 orientations of rotation. With the development of depth sensor cameras, we segmented possible hand regions by a depth value of interest and tracked the hand locations with a combination of frame difference, connected components, and centroid calculation. In recognition, we analyzed the moving hand path by line, circle, and ellipse approximation. The proposed algorithm can be applied to the multi-view 3D synthesis display system and the defined gestures can be used for 3D model view control. The overall accuracy was 92.58% with over a 150 Hz gesture report rate. Furthermore, the swipe identification showed an accuracy of 84.5% on the 4 swipe gestures of the challenging DHG-14/28 dataset. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/640007 | ISBN: | 9798350314694 | DOI: | 10.1109/ECICE59523.2023.10383019 |
顯示於: | 電機工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。