Fast and reliable PCA-based temporal segmentation of video sequences

Jiri Filip, Michal Haindl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With significantly increasing number of archived movie sequences a need of their automatic indexation and annotation is raising. Robust and fast temporal segmentation of video sequences is one of the challenging research topics in this area. In this paper we propose a new temporal segmentation method of the video sequences based on PCA approach. Contrary to standard approaches based on histogram or motion field analysis the proposed method does not require any such a complex analysis. The method starts with sparse greyscale sampling and eigen-analysis of input sequence. A sum of absolute derivatives of temporal mixing coefficients of main eigen-images is then used as cuts detection feature, while dissolve transitions are detected by means of coefficients' specific behaviour. The functionality of the method was successfully tested on number of sequences ranging from artificial set of similar dynamic textures to professional documentary movies. Although, the results may not be unexpected, we believe that proposed method provides novel, very fast and reliable way of movie cuts detection. © 2008 IEEE.

Original languageEnglish
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
Publication statusPublished - 2008
Event2008 19th International Conference on Pattern Recognition - Tampa, FL, United States
Duration: 8 Dec 200811 Dec 2008

Conference

Conference2008 19th International Conference on Pattern Recognition
Abbreviated titleICPR 2008
CountryUnited States
CityTampa, FL
Period8/12/0811/12/08

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    Filip, J., & Haindl, M. (2008). Fast and reliable PCA-based temporal segmentation of video sequences. In 2008 19th International Conference on Pattern Recognition, ICPR 2008