2D animation comic character action generation technology based on biomechanics simulation and artificial intelligence
Abstract
AI can greatly improve the process of creating 2D character animations, especially for platformer games. The objective is to enhance visual effects quality and streamline production by incorporating biomechanics and AI-driven technology into the animation process. The current state of study shows that conventional 2D animation production has several problems, such as lengthy procedures, complicated technical requirements, and the requirement for human involvement. Both efficiency and innovation are limited by these limitations. To solve this problem, we suggest generating 2D character animations using AI-driven generative methods and biomechanics simulation. Consistently high-quality outcomes can be achieved by automating aspects of animation design. Improving animation industry innovation, streamlining production workflows, and decreasing manual labor are crucial. The viability of 2D animations generated by AI has been demonstrated in preliminary studies. Artificial intelligence’s effects on animation’s expressiveness, realism, and aesthetics are covered in detail. Furthermore, it has presented challenges with training data, choosing the right model, and fine-tuning. Beyond the field of gaming, our research has wider implications. Several industries may benefit from the benefits of 2D animations enhanced with AI and biomechanics technology. These industries include advertising, entertainment, and education.
References
1. Shi D, Sun F, Xu X, et al. AutoClips: An Automatic Approach to Video Generation from Data Facts. Computer Graphics Forum. 2021; 40(3): 495-505. doi: 10.1111/cgf.14324
2. Du J. Comparison between 3D animation design and 2D animation design. Atlantis Press; 2021.
3. Hilsmann A, Fechteler P, Morgenstern W, et al. Going beyond free viewpoint: creating animatable volumetric video of human performances. IET Computer Vision. 2020; 14(6): 350-358. doi: 10.1049/iet-cvi.2019.0786
4. McClanahan S. A Day in the Life: Kkandbabyj, An Exploration of Three-Dimensional Design Processes to Convey Character Dynamics [PhD thesis]. The University of Texas at Dallas; 2023.
5. Soliman MM, Ahmed E, Darwish A, et al. Artificial intelligence powered Metaverse: analysis, challenges and future perspectives. Artificial Intelligence Review. 2024; 57(2). doi: 10.1007/s10462-023-10641-x
6. Hubble A, Moorin J, & Khuman AS. Artificial intelligence in fps games: NPC difficulty effects on gameplay. Springer International Publishing; 2021.
7. Górriz JM, Álvarez-Illán I, Álvarez-Marquina A, et al. Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends. Information Fusion. 2023; 100: 101945. doi: 10.1016/j.inffus.2023.101945
8. Westera W, Prada R, Mascarenhas S, et al. Artificial intelligence moving serious gaming: Presenting reusable game AI components. Education and Information Technologies. 2019; 25(1): 351-380. doi: 10.1007/s10639-019-09968-2
9. Tao G, Garrett B, Taverner T, et al. Immersive virtual reality health games: a narrative review of game design. Journal of NeuroEngineering and Rehabilitation. 2021; 18(1). doi: 10.1186/s12984-020-00801-3
10. Cheng L, Varshney KR, Liu H. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges. Journal of Artificial Intelligence Research. 2021; 71: 1137-1181. doi: 10.1613/jair.1.12814
11. Xu H, Bazavan EG, Zanfir A, et al. Ghum & Ghuml: Generative 3D Human Shape and Articulated Pose Models. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020. doi: 10.1109/cvpr42600.2020.00622
12. Khan S, Ali S, Khan A, et al. Inkjet printing of multi-stripes based deflection monitoring sensor on flexible substrate. Sensors and Actuators A: Physical. 2021; 323: 112638. doi: 10.1016/j.sna.2021.112638
13. Lahiri A, Kwatra V, Frueh C, et al. LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021. doi: 10.1109/cvpr46437.2021.00278
14. Sgambato BG, Hasbani MH, Barsakcioglu DY, et al. High Performance Wearable Ultrasound as a Human-Machine Interface for Wrist and Hand Kinematic Tracking. IEEE Transactions on Biomedical Engineering. 2024; 71(2): 484-493. doi: 10.1109/tbme.2023.3307952
15. Pichlmair M, Johansen M. Designing Game Feel: A Survey. IEEE Transactions on Games. 2022; 14(2): 138-152. doi: 10.1109/tg.2021.3072241
16. Wu Y, Yi A, Ma C, et al. Artificial intelligence for video game visualization, advancements, benefits and challenges. Mathematical Biosciences and Engineering. 2023; 20(8): 15345-15373. doi: 10.3934/mbe.2023686
17. Bai Y, Kaufman DM, Liu CK, et al. Artist-directed dynamics for 2D animation. ACM Transactions on Graphics. 2016; 35(4): 1-10. doi: 10.1145/2897824.2925884
18. Choi JI, Kim SK, Kang SJ. Image Translation Method for Game Character Sprite Drawing. Computer Modeling in Engineering & Sciences. 2022; 131(2): 747-762. doi: 10.32604/cmes.2022.018201
19. Sierra Rativa A, Postma M, Van Zaanen M. The Influence of Game Character Appearance on Empathy and Immersion: Virtual Non-Robotic Versus Robotic Animals. Simulation & Gaming. 2020; 51(5): 685-711. doi: 10.1177/1046878120926694
20. Farahani J, Soltani P, Roberts RE. Expertise differences in a 2D animation simulation decision-making task: The influence of presentation speed on performance. Real-World Applications in Cognitive Neuroscience. 2020; 87-100. doi: 10.1016/bs.pbr.2020.06.017
21. Zufri T, Hilman D, Frans O. Research on the Application of Pixel Art in Game Character Design. Journal of Games, Game Art, and Gamification. 2022; 7(1): 27-31. doi: 10.21512/jggag.v7i1.8565
22. Willett NS, Shin HV, Jin Z, et al. Pose2Pose. Association for Computing Machinery; 2020. pp. 88-99.
23. Subramonyam H, Li W, Adar E, et al. TakeToons. Association for Computing Machinery; 2018.
24. Stone M, DeCarlo D, Oh I, et al. Speaking with hands. ACM Transactions on Graphics. 2004; 23(3): 506-513. doi: 10.1145/1015706.1015753
25. Yan X. Research on the Design of Game Character with the Chinese Traditional Culture Characteristics. International Journal of Business and Social Science. 2016; 7(4): 260-264.
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