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Improving realism in automated fingerspelling of American sign language

机译：改善美国手语自动化手指的现实主义

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摘要

Fingerspelling is a process of communicating letters of a spoken language alphabet using a person's hand or hands. Portraying animations of fingerspelling has proved surprisingly resistant to automation because of the collisions that arise from conventional interpolation of keyframes of individual manual letters. Previous methods have not been able to provide convincingly realistic fingerspelling due to the absence of effective collision avoidance in the underlying animation algorithms. This paper reports on the development and evaluation of a new collision avoidance algorithm that aids fingerspelling. Instead of analyzing letter transitions, the algorithm capitalizes on the transitions of individual fingers. The new strategy is efficient enough to support real-time fingerspelling while still maintaining a high level of predictive accuracy. Utilizing this strategy in signing avatars is expected to improve the current resources for deaf children, hearing teachers, hearing parents, and interpreting students who want to improve their fingerspelling comprehension. Future work will include testing the strategy's generality when applying it to other one-handed manual alphabets.
机译：FingersPlate是使用人的手或手来沟通口语字母的字母。由于从个人手动字母的关键帧的传统插值产生的碰撞，因此证明了手指展示的动画令人惊讶地抵抗自动化。由于在潜在的动画算法中没有有效的碰撞避免，之前的方法没有能够提供令人信服的指尖。本文报告了一种新的避孕算法的开发和评价，辅助手指凹凸。该算法而不是分析信件转换，而是大写单个手指的过渡。新策略足以满足实时手指，同时仍保持高水平的预测精度。预计利用该策略在签署的头像中预计将改善目前聋儿的资源，听证教师，听证父母，并解释想要改善他们的手指的理解的学生。将来的工作将包括在将策略的一般性上施加到其他单手手动字母表中测试。

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