RC-SMPL : Real-time Cumulative SMPL-based Avatar Body Generation (IEEE ISMAR 2023)

Hail Song, Boram Yoon, Woojin Cho, Woontack Woo

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Abstract : We present a novel method for avatar body generation that cumulatively updates the texture and normal map in real-time. Multiple images or videos have been broadly adopted to create detailed 3D human models that capture more realistic user identities in both Augmented Reality (AR) and Virtual Reality (VR) environments. However, this approach has a higher spatiotemporal cost because it requires a complex camera setup and extensive computational resources. For lightweight reconstruction of personalized avatar bodies, we design a system that progressively captures the texture and normal values using a single RGBD camera to generate the widely-accepted 3D parametric body model, SMPL-X. Quantitatively, our system maintains real-time performance while delivering reconstruction quality comparable to the state-of-the-art method. Moreover, user studies reveal the benefits of real-time avatar creation and its applicability in various collaborative scenarios. By enabling the production of high-fidelity avatars at a lower cost, our method provides more general way to create personalized avatar in AR/VR applications, thereby fostering more expressive self-representation in the metaverse.

Effects of Different Facial Blendshape Combinations on Social Presence for Avatar-mediated Mixed Reality Remote Communication (IEEE ISMAR 2023 Poster)

Seoyoung Kang, Hail Song, Boram Yoon, Kangsoo Kim, Woontack Woo


Abstract : Despite the significance of facial expressions in avatar-mediated communication, there has been limited research on efficiently representing avatar facial expressions, encompassing both computational and communicative considerations. To address this, we first conduct an analysis of facial blendshapes, where we select those based on activation variance during natural conversations and their significance in conveying emotions. From two distinct selection approaches, we then investigate the impacts of four different facial blendshape combinations on social presence and communication quality in varied avatar-mediated remote communication contexts: informative speech and emotional conversation. The results of our formal study with 32 participants highlight the importance of emotion-based blendshapes, indicating that the emotionally essential blendshapes combination achieves comparable levels of social presence, facial animation realism, communication quality, and synchrony of communication cues compared to using the full set of blendshapes. Our findings emphasize the potential of a cost-efficient method for avatar facial control, enabling effective emotional expressions while reducing computational resources, ultimately resulting in more affordable and efficient avatar-mediated communication experiences.

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