Video Key Frame Extraction Using Optical Flow Method

This repository provides MATLAB source code for extracting video key frames using optical flow method. The code serves as the implementation for our research paper on content-based video retrieval and is available for reference purposes.

In this implementation, we employ optical flow method to extract key frames from video sequences. Optical flow is a computer vision technique that calculates pixel-level motion information between consecutive frames in an image sequence. The core algorithm analyzes pixel intensity changes between adjacent frames to compute motion vectors for each pixel, thereby tracking object movement trajectories. Our MATLAB implementation utilizes the Horn-Schunck or Lucas-Kanade optical flow algorithms (depending on configuration) to calculate motion vectors and applies threshold-based filtering to identify significant motion changes that indicate key frames.

This codebase corresponds to our content-based video retrieval research paper. Content-based retrieval analyzes visual content features for search and matching operations. Our proposed method leverages optical flow-derived key frames and implements frame similarity comparison using histogram analysis or feature matching techniques. The experimental results demonstrate effective retrieval performance, making this implementation a valuable reference for video retrieval research.

For researchers interested in key frame extraction, optical flow methods, or content-based video retrieval, this source code provides a practical implementation for study and experimentation. The code includes modular functions for video processing, optical flow computation, and similarity measurement. We hope this implementation proves useful for your research and provides insights for related computer vision applications.