An Empirical Comparison of Video Frame Sampling Methods for Multi-Modal RAG Retrieval

Understand

Numerous video frame sampling methodologies detailed in the literature present a significant challenge in determining the optimal video frame method for Video RAG pattern without a comparative side-by-side analysis.

• In this work, we investigate the trade-offs in frame sampling methods for Video & Frame Retrieval using natural language questions.
• We explore the balance between the quantity of sampled frames and the retrieval recall score, aiming to identify efficient video frame sampling strategies that maintain high retrieval efficacy with reduced storage and processing demands.
• Our study focuses on the storage and retrieval of image data (video frames) within a vector database required by Video RAG pattern, comparing the effectiveness of various frame sampling techniques.