南京师大学报（自然科学版）2025，Vol.48Issue(2)：83-90,8.DOI:10.3969/j.issn.1001-4616.2025.02.009
VR中基于改进SIFT特征匹配的手势检测与跟踪
Gesture Detection and Tracking Based on Improved SIFT Feature Matching in VR
摘要
Abstract
With the rapid development of virtual reality(VR)technology,the demand for natural human-computer interaction is increasing,and gesture recognition technology plays a crucial role.It not only requires high accuracy,but also must ensure real-time response to ensure that users can have a smooth interactive experience.This study proposes an innovative gesture detection and tracking method based on an improved Scale Invariant Feature Transform(SIFT)feature matching technique,specifically optimized for gesture recognition in VR environments.Firstly,this article has made in-depth improvements to the SIFT algorithm by introducing advanced descriptors to enhance feature discrimination,which enables the algorithm to more accurately capture key features of gestures.Then,in order to further improve the accuracy of matching,we carefully designed a feature matching strategy,optimized the correspondence between feature points,and ensured efficient matching even in complex scenes.Finally,in response to the real-time requirements,this article developed an algorithm optimization strategy that ensures efficient and stable operation of the algorithm even in dynamic and changing environments by adjusting the algorithm flow and calculation methods,thus meeting the application needs of real-time gesture tracking.The experimental results show that the prediction accuracy of the proposed model is 0.926,demonstrating excellent predictive performance.关键词
虚拟现实/手势检测/改进SIFT算法/特征匹配/人机交互Key words
virtual reality/gesture detection/improve SIFT algorithm/feature matching/human-computer interaction分类
计算机与自动化引用本文复制引用
苏琳,邹静,许媚..VR中基于改进SIFT特征匹配的手势检测与跟踪[J].南京师大学报（自然科学版）,2025,48(2):83-90,8.基金项目
福建省自然科学基金面上项目(2023J011406). （2023J011406）
