Video Shot Clustering using Spectral Methods

Abstract

The automatic segmentation and structuring of videos present technical challenges due to the large variation of content, spatial layout, and possible lack of storyline. In this paper, we propose a spectral method to group video shots into scenes based on their visual similarity and temporal relations. Spectral methods have been shown to be effective in capturing perceptual organization features. In particular, we investigate the problem of automatic model selection, which is currently an open research issue for spectral methods, and propose measures to assess the validity of a grouping result. The methodology is used to group shots from home videos and soccer games. The results indicate the validity of the proposed approach, both compared to existing techniques as well as to human performance.