TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Video characterization based on activity clustering

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko8th International Conference on Electrical and Computer Engineering: Advancing Technology for a Better Tomorrow, ICECE 2014
KustantajaThe Institute of Electrical and Electronics Engineers, Inc.
Sivut266-269
Sivumäärä4
ISBN (painettu)9781479941667
DOI - pysyväislinkit
TilaJulkaistu - 28 tammikuuta 2015
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
Tapahtuma8th International Conference on Electrical and Computer Engineering, ICECE 2014 - Dhaka, Bangladesh
Kesto: 20 joulukuuta 201422 joulukuuta 2014

Conference

Conference8th International Conference on Electrical and Computer Engineering, ICECE 2014
MaaBangladesh
KaupunkiDhaka
Ajanjakso20/12/1422/12/14

Tiivistelmä

In this paper, we propose a method for video characterization based on activity description information. We employ a state-of-the-art video representation in order to learn human activity concepts, i.e., video groups formed by videos depicting similar human activities. In order to exploit the enriched visual information that is available in multi-view settings, we propose the use of the circular shift invariance property of the coefficients of the Discrete Fourier Transform (DFT) that leads to a view-independent multi-view action representation. In the test phase, in order to assign a test video to one (or multiple) activity groups, we perform temporal video segmentation in order to determine shorter videos depicting simple actions. Experimental results on 2 multi-view action databases denote the effectiveness of the proposed approach.