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Linear algebra for vision-based surveillance in heavy industry - convergence behavior case study | IEEE Conference Publication | IEEE Xplore

Linear algebra for vision-based surveillance in heavy industry - convergence behavior case study


Abstract:

The surveillance application aims at improving the quality of technology via modelling human expert behaviour in the coking plant ArcelorMittal Ostrava, the Czech Republi...Show More

Abstract:

The surveillance application aims at improving the quality of technology via modelling human expert behaviour in the coking plant ArcelorMittal Ostrava, the Czech Republic. Video data on several industrial processes are captured by means of a CCD camera and classified by using Latent Semantic Indexing (LSI) with the respect to etalons classified by an expert. We also study the convergence behavior of proposed partial eigenproblem-based dimension reduction technique and its ability for knowledge acquisition. Having increased the computational effort of the dimension reduction technique did not imply the increasing quality of retrieved results in our cases.
Date of Conference: 18-20 June 2008
Date Added to IEEE Xplore: 15 July 2008
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Conference Location: London, UK

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