Artificial Intelligence Scene Creation with Virtual Technology for the DigitalFilm
DOI:
https://doi.org/10.69996/jcai.2024025Keywords:
Artificial Intelligence, Scene Creation, Digital Media, classification, Visual SystemAbstract
Artificial Intelligence-based scene creation leverages advanced algorithms to generate realistic
and immersive environments for various applications, including gaming, virtual reality, and simulations.
By utilizing techniques such as procedural generation, deep learning, and computer vision, these systems
can automatically create complex landscapes, detailed textures, and dynamic elements that respond to
user interactions. This not only enhances the user experience but also significantly reduces the time and
effort required for manual scene design, enabling developers to focus on creativity and innovation. In the
realm of digital media production, the quest for lifelike scenes and efficient evaluation methodologies has
led to the exploration of novel techniques. This paper investigates the synergy between point estimation
and artificial intelligence (AI) in advancing digital scene creation and evaluation. Through comprehensive
simulations and analyses, we assess the effectiveness of point estimation in quantifying scene attributes
such as visual realism, dynamic interactivity, physical accuracy, and artistic expression. Additionally, we
delve into the utilization of AI algorithms for automating scene classification, thereby streamlining
decision-making processes and optimizing resource allocation in production workflows. Through
comprehensive simulations and analyses, we assess the effectiveness of point estimation in quantifying
scene attributes such as visual realism (mean score: 0.85), dynamic interactivity (mean score: 0.72),
physical accuracy (mean score: 0.93), and artistic expression (mean score: 0.65).
References
1. A. A.Abdelhamid, E. S. M. El-Kenawy, B. Alotaibi, G. M. Amer, M. Y. Abdelkader et al., “Robust speech emotion recognition using CNN+ LSTM based on stochastic fractal search optimization algorithm,” IEEE Access, vol.10, pp.49265-49284, 2022.
2. M. A.Khan, S. Abbas, A. Raza, F. Khan and T. Whangbo, “Emotion Based Signal Enhancement Through Multisensory Integration Using Machine Learning,” Computers, Materials & Continua, vol.71, no.3, 2022.
3. Y. Bao, “Application of virtual reality technology in film and television animation based on artificial intelligence background,” Scientific Programming, vol.2022, pp.1-8, 2022.
4. L. Sun, “Research on Digital Media Art Film and Television Special Effects Technology Based on Virtual and Reality Algorithm,” Scientific Programming, vol.2022, 2022.
5. R. Jiang, L. Wang and S.B. Tsai, “An empirical study on digital media technology in film and television animation design,” Mathematical Problems in Engineering, vol.2022, pp.1-10, 2022.
6. C. Du, C. Yu, T. Wang and F. Zhang, “Impact of virtual imaging technology on film and television production education of college students based on deep learning and internet of things,” Frontiers in Psychology, vol.12, pp.766634, 2022.
7. L. Li, “The influence of digital twins on the methods of film and television creation,” Computers and Electrical Engineering, vol.103, pp.108314, 2022.
8. C. Cremona and M. Kavakli, “The Evolution of the Virtual Production Studio as a Game Changer in Filmmaking,” In Creating Digitally: Shifting Boundaries: Arts and Technologies— Contemporary Applications and Concepts, pp. 403-429, 2023.
9. X. Yuan and H. Huixuan, “The Fusion Method of Virtual Reality Technology and 3D Movie Animation Design,” International Journal of Advanced Computer Science & Applications, vol.14, no.11, 2023.
10. W. Xiong, “Construction of Teaching Mode of Film and TV Art in Institution of Higher Learning Using Virtual Simulation Technology,” Computational Intelligence and Neuroscience, vol. 2022, 2022.
11. M. Kavakli and C. Cremona, “The virtual production studio concept–an emerging game changer in filmmaking,” In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Christchurch, New Zealand, pp. 29-37, 2022.
12. W. Zhao, S. Zhang and X. Li, “Impact of virtual reality technology on digital media in the context of big data and artificial intelligence,” Journal of Computational Methods in Sciences and Engineering, vol.23, no.2, pp.605-615, 2023.
13. L. Jiang, “Application of Neural Network and Virtual Reality Technology in Digital Video Effects,” International Transactions on Electrical Energy Systems, vol. 2022, 2022.
14. P. Chanpum, “Virtual production: Interactive and real-time technology for filmmakers,” Humanities, Arts and Social Sciences Studies, 9-17, 2023.
15. L. Song, “Research on the Application of Computer 3D Technology in the Creation of Films Adapted from Literary Works,” In 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), Dalian, China, pp. 1461-1465, 2022.
16. X. Xu, H. Yan and X. Wang, “Research on Postproduction of Film and Television Based on Computer Multimedia Technology,” Scientific Programming, vol.2022, 2022.
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