# Real-Time Interaction for 3D Pixel Human in Virtual Environment
## 6 Discussion  
The main goal of our study is to develop an avatar that expresses the characteristics of users in 3D virtual meetings and interactions and has a good sense of contact and spatial coexistence. In a comparative experiment based on a user study considering several baseline methods, we first proved that our method has the same advantages as a 2D video conference, which can reflect the realistic features of user expression and clothing. Additionally, similar to an artificial avatar, our method has the advantage of a more direct interaction experience in a 3D virtual space. Figure 13 shows multi-person interactions with virtual objects using pixel avatars in a virtual meeting. Overall, our method is more comprehensive than the baseline methods. We also verified the simplicity and effectiveness of our system through SUS questionnaire experiments and proved the effectiveness of each component of our framework through different supplemental experiments. We aim to apply pixel avatars to multi-person virtual conferences and virtual interaction scenarios. Although we built a multi-person interaction scene as shown in Figure 13, we only performed single-person experiments interacting with virtual objects and real-time avatar generation experiments for consistency and objectiveness. There is no comparative experiment with other avatar types on communication efficiency through various non-verbal communication means, such as body language, in multi-person scenarios. In the future, we plan to further improve the pixel avatar and its generation method and conduct a more detailed comparison between the pixel avatar and other existing methods in multi-person scenarios. In the avatar generation speed test, the time required to obtain the data needed to visualize the pixel avatar through the entire human video stream processing has no noticeable difference for the four avatars of different resolutions, all of which are in the range of 37 ms to 40 ms. The significant differences in the generation speed between the high-resolution avatar and the low-resolution avatar are mainly caused by the visualization part of the pixel avatar, which is the performance bottleneck of our method. While implementing avatar visualization, we represent each pixel of the body image by a particle of Unity's particle system, and the excessive particle number of 320 \(\times\) 240 resolution avatar leads to a significant drop in speed. A more efficient rendering method to visualize pixel avatars would significantly improve the overall performance of representing avatars, which is a key part of our future work. According to our results and analysis, the body of a low-resolution pixel avatar is closer to the style of pixel art, but it does not match a high-resolution head. In contrast, a high-resolution pixel avatar body point cloud is more consistent with a high-resolution head but loses the pixel art style of the avatar. Based on the user preferences for higher  
Figure 13: Multi-person use pixel avatars to interact with virtual objects in virtual space. resolution avatars in our user survey, our current pixel-stylization method is not highly welcomed. We assumed that it is mainly caused by the resolution gap between the high-resolution head part and pixel-style body part. One possible solution is learning-based style transfer methods such as those used in [6; 12]. To make the avatar head and body style more unified and vivid, we assume that the learning-based pixel-style transfer method rather than the current algorithm method can express details of both the face and body more clearly. As some users may prefer high-resolution avatars to pixel-style art, another possible solution is improving the resolution of the pixel avatar to replicate a user's skin tone and clothing more accurately. As shown in the speed test, there is no significant difference between the human video stream processing time required for high-resolution avatars and low-resolution avatars. The final performance difference is mainly caused by the visualization stage.