Title :
Supervised and unsupervised classification post-processing for visual video summaries
Author :
Ciocca, Gianluigi ; Schettini, Raimondo
Author_Institution :
Dept. of IT, Syst. & Commun., Milano-Bicocca Univ., Milan, Italy
fDate :
5/1/2006 12:00:00 AM
Abstract :
Representation of the video content using a set of key frames is one of the most common techniques for video summarization. Summaries composed of key frames allow users to grasp the overall content of a video, and access specific sequences. The post-processing algorithm presented in this paper makes it possible to create visual video summaries that are exhaustive, but not redundant, in three steps the method removes meaningless key frames, groups the key frames into clusters to allow multi-level summary presentation, and determines the default summary level. The algorithm utilizes both supervised and unsupervised classification strategies to perform these tasks. It requires no previous knowledge about the video contents, nor is any assumption made about the input data.
Keywords :
image classification; image representation; video signal processing; classification post-processing algorithm; multilevel summary presentation; unsupervised classification strategies; video content representation; visual video summarization; Clustering algorithms; Gunshot detection systems; Image databases; Information retrieval; Layout; Multimedia databases; Multimedia systems; Resumes; Video sequences; Visual databases;
Journal_Title :
Consumer Electronics, IEEE Transactions on
DOI :
10.1109/TCE.2006.1649689