ADVANCEMENTS IN VIDEO CAPTIONING: A COMPREHENSIVE REVIEW OF DEEP LEARNING TECHNIQUES, ARCHITECTURES, AND PRE-PROCESSING STRATEGIES
International Research Journal of Modernization in Engineering Technology and Science · 2024
This research paper delves into the realm of video captioning using deep learning techniques, focusing on enhancing accessibility and comprehension of multimedia content.The introduction highlights the significance of video captioning in making content accessible to diverse audiences and outlines the manual transcription and automatic captioning methods.The literature review traces the evolution of video captioning, emphasizing the pivotal role of deep learning models and their impact on computer vision and natural language processing.The paper explores various deep learning techniques, including encoder-decoder architectures, transformerbased models, and multimodal fusion techniques, providing an overview of their architectures and advantages.The research methodology involves a systematic literature review, a comparative analysis of different techniques, and an investigation into pre-processing techniques, with a strong emphasis on ethical considerations.A comparative study table presents key research papers, authors, publication years, main focuses, and results, offering insights into the strengths and limitations of different video captioning approaches.The study evaluates pre-processing techniques such as temporal smoothing, text normalization, scene segmentation, and more, using performance metrics like accuracy, user comprehension rates, and caption readability scores.In conclusion, the paper highlights the continuous progress in video captioning through deep learning, emphasizing the importance of context understanding, domain-specific models, and collaboration between humans and smart systems.The future scope envisions improved model architectures, multimodal approaches, ethical considerations, and real-time processing, promising a dynamic and inclusive future for video captioning.