基于语音和情感数据的面部数据收集优化方法用于人-虚拟角色重建
Streamlined Facial Data Collection based on Utterance and Emotional Data for Human-to-Avatar Reconstruction
AI总结：
本文提出基于语音和情感数据的面部数据收集优化方法，通过实验表明针对性数据能高效重建虚拟角色，减少训练时间和数据使用，适用于AR/VR远程存在等实时应用。
摘要：
本研究探索了一种用于对话场景的简化面部数据收集方法，针对现有方法常常需要大量数据集且优先考虑技术指标而非用户感知和体验的局限性。我们系统地研究了哪些面部表情数据对于重建逼真虚拟角色至关重要，以及如何高效地捕捉这些数据。我们的研究采用两阶段方法来识别高效的面部数据收集策略并评估其有效性。第一阶段中，我们进行面部数据采集，并使用语音数据和情感数据评估重建性能。第二阶段中，我们进行了全面的用户评估，比较三种渐进条件：仅语音、语音和情感数据以及包含大量数据的对照条件。24名参与模拟面对面对话的受试者的结果表明，针对的语音和情感数据在感知真实感、自然度和远程存在感方面达到可比水平，同时在训练时间和数据使用方面相比大量数据收集方法有所减少。这些结果证明，有针对性的数据输入可以实现高效的虚拟角色面部重建，为实时应用如AR/VR远程存在提供了实用指南，并突显了数据量与感知质量之间的权衡。
英文摘要：
This study explores a streamlined facial data collection method for conversational contexts, addressing the limitations of existing approaches that often require extensive datasets and prioritize technical metrics over user perception and experience. We systematically investigate which facial expression data are essential for reconstructing photorealistic avatars and how they can be captured efficiently. Our research employs a two-phase methodology to identify efficient facial data collection strategies and evaluate their effectiveness. In the first phase, we conduct facial data acquisition and evaluate reconstruction performance using utterance data and emotional data. In the second phase, we carry out a comprehensive user evaluation comparing three progressive conditions: utterance only, utterance and emotional data, and a control condition involving extensive data. Findings from 24 participants engaged in simulated face-to-face conversations reveal that targeted utterance and emotional data achieve comparable levels of perceived realism, naturalness, and telepresence, while reducing training time and data usage when compared to the extensive data collection approach. These results demonstrate that targeted data inputs can enable efficient avatar face reconstruction, offering practical guidelines for real-time applications such as AR/VR telepresence and highlighting the trade-off between data quantity and perceived quality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
