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

arXiv: https://arxiv.org/abs/1405.0174 · HTML: https://mlsanity.com/paper/1405.0174/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 May 2014.

## Built on by (most cited first, 3 of 3)

- [Learning Segment Similarity and Alignment in Large-Scale Content Based Video Retrieval](https://mlsanity.com/paper/2309.11091/) (2023)
- [Cluster-based Video Summarization with Temporal Context Awareness](https://mlsanity.com/paper/2404.04511/) (2024)
- [Video Summarization Techniques: A Comprehensive Review](https://mlsanity.com/paper/2410.04449/) (2024)

## Abstract (arXiv)

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.