VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering

TL;DR

VSCAN introduces a novel density-based clustering method that combines color and texture features to generate higher-quality static video summaries, outperforming existing approaches in evaluation.

Contribution

The paper presents VSCAN, an innovative video summarization technique using a modified DBSCAN algorithm with combined color and texture features.

Findings

VSCAN produces summaries with higher quality than existing methods.

Experimental results validate the effectiveness of the combined feature approach.

VSCAN outperforms other approaches in evaluation metrics.

Abstract

In this paper, we present VSCAN, a novel approach for generating static video summaries. This approach is based on a modified DBSCAN clustering algorithm to summarize the video content utilizing both color and texture features of the video frames. The paper also introduces an enhanced evaluation method that depends on color and texture features. Video Summaries generated by VSCAN are compared with summaries generated by other approaches found in the literature and those created by users. Experimental results indicate that the video summaries generated by VSCAN have a higher quality than those generated by other approaches.