OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation

TL;DR

OmniDataComposer introduces a unified data structure that fuses multimodal data like video, audio, and text, enabling comprehensive data processing, generation, and improved AI understanding of complex real-world information.

Contribution

It presents a novel cohesive data structure and algorithm for multimodal data fusion and unlimited data generation, broadening object recognition and enhancing cross-modal interactions.

Findings

Capable of identifying over 6400 object categories

Transforms videos into detailed sequential documents

Facilitates high-quality dataset creation for AI models

Abstract

This paper presents OmniDataComposer, an innovative approach for multimodal data fusion and unlimited data generation with an intent to refine and uncomplicate interplay among diverse data modalities. Coming to the core breakthrough, it introduces a cohesive data structure proficient in processing and merging multimodal data inputs, which include video, audio, and text. Our crafted algorithm leverages advancements across multiple operations such as video/image caption extraction, dense caption extraction, Automatic Speech Recognition (ASR), Optical Character Recognition (OCR), Recognize Anything Model(RAM), and object tracking. OmniDataComposer is capable of identifying over 6400 categories of objects, substantially broadening the spectrum of visual information. It amalgamates these diverse modalities, promoting reciprocal enhancement among modalities and facilitating cross-modal data correction. \textbf{The final output metamorphoses each video input into an elaborate sequential document}, virtually transmuting videos into thorough narratives, making them easier to be processed by large language models. Future prospects include optimizing datasets for each modality to encourage unlimited data generation. This robust base will offer priceless insights to models like ChatGPT, enabling them to create higher quality datasets for video captioning and easing question-answering tasks based on video content. OmniDataComposer inaugurates a new stage in multimodal learning, imparting enormous potential for augmenting AI's understanding and generation of complex, real-world data.