Publication Type:

Conference Proceedings

Source:

Advances in Intelligent Systems and Computing, Volume 573, p.494-506 (2017)

ISBN:

9783319572604

URL:

https://www.researchgate.net/publication/315865021_Application_of_Clustering_Techniques_for_Video_Summarization_-_An_Empirical_Study

Abstract:

Identification of relevant frames from a video which can then be used as a summary of the video itself, is a challenging task. An attempt has been made in this study to empirically evaluate the effectiveness of data mining techniques in video summarization. Video Summarization systems based on histogram and entropy features extracted from three different color spaces: RGB, HSV and YCBCR and clustered using K-Means, FCM, GM and SOM were empirically evaluated on fifty video datasets from the VSUMM [1] database. Results indicate that clustering based video summarizations techniques can be effectively used for generating video summaries

Cite this Research Publication

A. John, Dr. Binoy B. Nair, and Dr. (Col.) Kumar P. N., “Application of Clustering Techniques for Video Summarization – An Empirical Study”, Advances in Intelligent Systems and Computing, vol. 573. pp. 494-506, 2017.