The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
JALI: an animator-centric viseme model for expressive lip synchronization
Abstract
The rich signals we extract from facial expressions imposes high expectations for the science and art of facial animation. While the advent of high-resolution performance capture has greatly improved realism, the utility of procedural animation warrants a prominent place in facial animation workflow. We present a system that, given an input audio soundtrack and speech transcript, automatically generates expressive lip-synchronized facial animation that is amenable to further artistic refinement, and that is comparable with both performance capture and professional animator output. Because of the diversity of ways we produce sound, the mapping from phonemes to visual depictions as visemes is many-valued. We draw from psycholinguistics to capture this variation using two visually distinct anatomical actions: Ja w and L ip, wheresound is primarily controlled by jaw articulation and lower-face muscles, respectively. We describe the construction of a transferable template jali 3D facial rig, built upon the popular facial muscle action unit representation facs. We show that acoustic properties in a speech signal map naturally to the dynamic degree of jaw and lip in visual speech. We provide an array of compelling animation clips, compare against performance capture and existing procedural animation, and report on a brief user study.
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Ekman, P., & Friesen, W. V. (2019) · PsycTESTS Dataset · doi:10.1037/t27734-000 · Cited by 6,019
Video Rewrite: driving visual speech with audio
Bregler, C., Covell, M., & Slaney, M. (1997) · Proceedings of the 24th annual conference on Computer graphics and interactive techniques - SIGGRAPH '97 · doi:10.1145/258734.258880 · Cited by 669
Cited by
AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis
Guo, Y., Chen, K., Liang, S., Liu, Y.-J., Bao, H., & Zhang, J. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00573 · Cited by 384
Capture, Learning, and Synthesis of 3D Speaking Styles
Cudeiro, D., Bolkart, T., Laidlaw, C., Ranjan, A., & Black, M. J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01034 · Cited by 365
Text-based Editing of Talking-head Video
Fried, O., Tewari, A., Zollhöfer, M., Finkelstein, A., Shechtman, E., Goldman, D. B., Genova, K., Jin, Z., Theobalt, C., & Agrawala, M. (2019) · ACM Transactions on Graphics · doi:10.1145/3306346.3323028 · Cited by 270
EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model
Ji, X., Zhou, H., Wang, K., Wu, Q., Wu, W., Xu, F., & Cao, X. (2022) · Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings · doi:10.1145/3528233.3530745 · Cited by 155
Artificial intelligence moving serious gaming: Presenting reusable game AI components
Westera, W., Prada, R., Mascarenhas, S., Santos, P. A., Dias, J., Guimarães, M., Georgiadis, K., Nyamsuren, E., Bahreini, K., Yumak, Z., et al. (2020) · Education and Information Technologies · doi:10.1007/s10639-019-09968-2 · Cited by 136
Metadata
- Authors
- Edwards, P., Landreth, C., Fiume, E., & Singh, K.
- Venue
- ACM Transactions on Graphics
- Published
- 2016-07-11
- Volume
- 35
- Issue
- 4
- Pages
- 1-11
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2468212864
- Cited by
- 184
- References
- 2
- FWCI
- 6.73
- Type
- journal article
- Language
- en
- Open access
- closed
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