Unsupervised Activity Extraction on Long-Term Video Recordings employing Soft Computing Relations - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2011

Unsupervised Activity Extraction on Long-Term Video Recordings employing Soft Computing Relations

Abstract

In this work we present a novel approach for activity extraction and knowledge discovery from video employing fuzzy relations. Spatial and temporal properties from detected mobile objects are modeled with fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows finding spatio-temporal patterns of activity. We present results obtained on videos corresponding to different sequences of apron monitoring in the Toulouse airport in France.
Fichier principal
Vignette du fichier
ICVS2011_patino_hal.pdf (141.49 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00650048 , version 1 (09-12-2011)

Identifiers

  • HAL Id : hal-00650048 , version 1

Cite

Jose Luis Patino Vilchis, Murray Evans, James Ferryman, François Bremond, Monique Thonnat. Unsupervised Activity Extraction on Long-Term Video Recordings employing Soft Computing Relations. 8th International Conference on Computer Vision Systems, ICVS 2011, Sep 2011, Sophia Antipolis, France. ⟨hal-00650048⟩

Collections

INRIA INRIA2
128 View
151 Download

Share

Gmail Facebook X LinkedIn More