CoolMoves
CoolMoves
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酷动
DOI：
10.1145/3463499
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发表时间：
2021
影响因子：
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通讯作者：
Andrew D. Wilson
中科院分区：
文献类型：
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作者：
Karan Ahuja;Mar González;Andrew D. Wilson
当前的虚拟现实（VR）系统缺乏对用户运动的风格化和修饰-这些概念已经在游戏和电影的动画中得到了很好的探索。我们提出了CooIMoves，一个系统的表达和强调全身运动合成的用户的虚拟化身在实时的，从有限的输入线索提供当前的消费级VR系统，特别是耳机和手的位置。我们利用现有的运动捕捉数据库作为模板运动库提请。我们匹配数据库中存在的类似的时空运动，然后使用加权距离度量在它们之间进行插值。联合预测概率，然后使用时间平滑的合成运动，使用人体运动动力学作为先验。这使得我们的系统即使在非常稀疏的运动数据库（例如，每个动作只有3-5个动作）。我们通过四个实验验证了我们的系统：我们的定量姿态重建的技术评估和三个额外的用户研究，以评估运动质量，体现和机构。
Current Virtual Reality (VR) systems are bereft of stylization and embellishment of the user's motion - concepts that have been well explored in animations for games and movies. We present CooIMoves, a system for expressive and accentuated full-body motion synthesis of a user's virtual avatar in real-time, from the limited input cues afforded by current consumer-grade VR systems, specifically headset and hand positions. We make use of existing motion capture databases as a template motion repository to draw from. We match similar spatio-temporal motions present in the database and then interpolate between them using a weighted distance metric. Joint prediction probability is then used to temporally smooth the synthesized motion, using human motion dynamics as a prior. This allows our system to work well even with very sparse motion databases (e.g., with only 3-5 motions per action). We validate our system with four experiments: a technical evaluation of our quantitative pose reconstruction and three additional user studies to evaluate the motion quality, embodiment and agency.
影响因子：
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作者：
Peck, Tabitha C.;Gonzalez-Franco, Mar
通讯作者：
Gonzalez-Franco, Mar