Shot boundary detection and key-frame extraction from neurosurgical video sequences

Abstract

In this work, we present a system for video shot boundary detection and key-frame extraction from video sequences based on colour histograms. The growth of archived video material has made automated indexing and browsing tools necessary. The aim of this paper is to provide a framework for such a video indexing and browsing tool. The proposed system segments video sequences based on colour similarity, and then extracts key-frames by clustering the images. Computations of colour histogram differences and self-similarity modelling have been performed in segmentation process. We have extracted three-, four- and five-frames video summaries with unsupervised k-means clustering. We have also dynamically determined the number of key-frames representing the video content without any prior information based on dominant set clustering. Our results show that our approach is successful in both segmentation and key-frame extraction processes.

Keywords:

• video segmentation
• shot boundary detection
• key-frame extraction
• video processing

The authors are to extend recognition to Professor G. Yasargil at the Neurosurgery Department of the University of Arkansas Medical Sciences for being inspirational and instrumental in the very early stage of the Neurosurgery Repository for Knowledge Dissemination idea.