VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering
This addresses the problem of creating static video summaries for users, but it appears incremental as it builds on existing clustering techniques.
The paper tackles video summarization by proposing VSCAN, a method using a modified DBSCAN clustering algorithm with color and texture features, and reports that it generates higher-quality summaries than other approaches.
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.