Motion Arc Analysis in Virtual Reality Environment
Chenxin Qu, Ruiling Chen, Xiaoping Che · 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) · 2022
With the popularity of VR, the body interaction in VR has not received enough corresponding attention, and the interaction design that violates the law of the human body happens a lot. Therefore, we study the action interaction in virtual reality through motion arc, an important parameter of human action, to get the factors that affect the user’s body interaction in virtual reality. A within-subject experiment (n=18) was conducted, in which all participants played three VR games and responded to the post-game questionnaire. Through video recordings of the front and right side of them, 3D skeleton modeling was reconstructed by using OpenPose and the conversion relationship between the four coordinate systems under computer vision. After the results of operations such as skeleton standardization and motion segmentation, clustering algorithms are used to cluster similar users, and Spearman’s Rank Correlation Coefficient is used to study the influence of user characteristics on motion arc. Our results indicated that in an unconstrained game, the tutorial makes the motion arc increase, while in a constrained game, the change of motion arc is more complex. It is also found that the participants’ instructions learning has the greatest impact on the average motion arc, followed by individual factors (including age gender, etc.) and sports experience.