Dimensionality Reduction for Distance Based Video Clustering

Abstract : Clustering of video sequences is essential in order to perform video summarization. Because of the high spatial and temporal dimensions of the video data, dimensionality reduction becomes imperative before performing Euclidean distance based clustering. In this paper, we present non-adaptive dimensionality reduction approaches using random projections on the video data. Assuming the data to be a realization from a mixture of Gaussian distributions allows for further reduction in dimensionality using random projections. The performance and computational complexity of the K-means and the K-hyperline clustering algorithms are evaluated with the reduced dimensional data. Results show that random projections with an assumption of Gaussian mixtures provides the smallest number of dimensions, which leads to very low computational complexity in clustering.
Type de document :
Communication dans un congrès
Harris Papadopoulos; Andreas S. Andreou; Max Bramer. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. Springer, IFIP Advances in Information and Communication Technology, AICT-339, pp.270-277, 2010, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-16239-8_36〉
Liste complète des métadonnées

Littérature citée [6 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01060677
Contributeur : Hal Ifip <>
Soumis le : jeudi 16 novembre 2017 - 15:59:36
Dernière modification le : dimanche 17 décembre 2017 - 01:11:24
Document(s) archivé(s) le : samedi 17 février 2018 - 14:11:10

Fichier

ThiagarajanRS10.pdf
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Jayaraman J. Thiagarajan, Karthikeyan N. Ramamurthy, Andreas Spanias. Dimensionality Reduction for Distance Based Video Clustering. Harris Papadopoulos; Andreas S. Andreou; Max Bramer. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. Springer, IFIP Advances in Information and Communication Technology, AICT-339, pp.270-277, 2010, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-16239-8_36〉. 〈hal-01060677〉

Partager

Métriques

Consultations de la notice

94

Téléchargements de fichiers

35