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Optimization of VR Human-computer Game Interaction Based on Improved PIFPAF Algorithm and Binocular Vision

Zhu Hong, Chen Bo

Machine Graphics and Vision

2025

Vol. 34, No. 3

3--30

To make virtual reality human-computer games more accurate and provide users with animmersive gaming experience, the study combines the method of improved part intensity field and partassociation field (PIFPAF) with binocular vision to optimize the interaction of VR human-computergames. The experimental results indicated that the PIFPAF algorithms performed relatively well withnumber of errors and target keypoint correlation of 0.22 and 0.97, respectively. In terms of processingspeed, the algorithm performed faster in both 640×480 and 320×240 resolutions, with 13 fps and 19 fps,respectively. Among the five predefined gestures, the “pointing” gesture was recognized correctly thelargest number of times in 30 test sessions, with 29 successful identifications. In contrast, the “clenchedfist” gesture had the fewest correct recognitions, totaling 26. The success of the suggested approachis confirmed by the experimental findings, which show that the optimized human-computer interactionsystem has high accuracy and processing speed. This study offers a fresh approach to the advancementof human-computer interaction technology and encourages technological integration innovation in therealm of virtual reality human-computer gaming.