Enhancing Image-Based Rendering Through Intelligent Machine Learning: Realism, Immersion, and Future Directions

Authors

  • Bheema Shanker Neyigapula1* 1Department of Information Technology, Jawaharlal Nehru Technological University, Hyderabad, India.

DOI:

https://doi.org/10.51483/IJAIML.3.2.2023.45-56

Keywords:

Image-based rendering, Machine learning, Deep learning, Reinforcement learning, Generative networks, View synthesis, Scene completion, Realism, Virtual reality, Gaming, Cinematography, Architectural visualization

Abstract

Image-Based Rendering (IBR) techniques have become essential for generating
realistic and immersive visual content, allowing users to explore scenes from
different viewpoints. This research paper proposes an innovative framework,
named Intelligent Image-Based Rendering (iIBR), that harnesses the power of
machine learning to enhance IBR capabilities. The framework integrates deep
learning models, reinforcement learning algorithms, and generative networks
to address challenges related to view synthesis, scene completion, and virtual
scene realism. Through extensive evaluation and comparisons with traditional
IBR approaches, the iIBR framework demonstrates superior performance,
adaptability, and potential applications in virtual reality, gaming,
cinematography, architectural visualization, and beyond.

Downloads

Published

2023-07-05

How to Cite

Bheema Shanker Neyigapula1*. (2023). Enhancing Image-Based Rendering Through Intelligent Machine Learning: Realism, Immersion, and Future Directions. International Journal of Artificial Intelligence and Machine Learning, 3(02), 45–56. https://doi.org/10.51483/IJAIML.3.2.2023.45-56

Similar Articles

<< < 1 2 3 4 5 6 > >> 

You may also start an advanced similarity search for this article.