# Real-Time Interaction for 3D Pixel Human in Virtual Environment
## 5 Experiments and Results
### Comparative Experiment
Both the 2D video conference and skeleton avatar can reflect the user's arm texture because they contain information from the user's 2D video stream, but because they are not 3D, they cannot reflect the arm shape. Therefore, the difference in scores between these two methods is not significant. Our method can reflect both texture and shape characteristics, and achieved the highest score. For Q2, which is related to the interaction experience, the results reported for our method (mean = 4.34, SD = 0.60) are significantly higher than those of the 2D video conference (mean = 2.50, SD = 1.10) (t(30) = 5.91, \(p<0.05\)), artificial avatar (mean = 2.78, SD = 1.02) (t(30) = 5.30, \(p<0.05\)), and skeleton avatar (mean = 3.63, SD = 0.62) (t(30) = 3.34, \(p<0.05\)). The 2D video conference yielded the lowest score when interacting with virtual objects because it cannot represent the interaction between the avatar's hand and the objects, so the feeling of contact is not apparent, particularly from the first-person perspective. The artificial avatar can represent the interaction between hands and virtual objects, but is limited by a lack of user image realism, so its score in the interactive experience is also lower than that of our pixel avatar. The interaction logic of the skeleton avatar is approximately the same as that of our method. The arm composed of balls and rods can accurately interact with virtual objects from both the first-person and third-person perspectives. Among the three baselines, the score of the skeleton avatar is the closest to that of our method. Compared to the skeleton avatar, our method can more accurately reflect the volume and texture of the arm from a first-person perspective, so the contact performance during interaction is more intuitive, resulting in the highest evaluation score. For Q3, the mean score of our method is 4.59 (SD = 0.71), which is higher than those of the 2D video conference (mean = 3.25, SD = 0.86), artificial avatar (mean = 0.94, SD = 0.77), and skeleton avatar (mean = 3.06, SD = 0.85). The results of our method are also significantly higher than those of the 2D video conference (t(30) = 4.83, \(p<0.05\)), artificial avatar (t(30) = 10.12, \(p<0.05\)), and skeleton avatar (t(30) = 5.51, \(p<0.05\)). These results indicate that our method is more similar to an offline face-to-face meeting compared to the other avatar-generation methods. While observing the avatars of other users in a virtual meeting from the third-person perspective, it is difficult for users to determine the identities of other participants in a conference while using artificial avatars, which affects the feeling of coexistence when meeting other users, resulting in the lowest score. Although 2D video conferences and skeleton avatars can reflect the person who a user is meeting, 2D video conferences lack the 3D sense of real people. The skeleton avatar has a pair of repeated arms, which differ from those of real people. Our method can more accurately recreate 3D conference participants compared to the baselines while reflecting the identities of participants in a conference, resulting in the highest score for the sense of spatial coexistence.