Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information

This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism of FMTHL and SGTs to deal with erroneous, missing, and noisy data and compl...

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Bibliographic Details
Main Author: Münch, David (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2017
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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020 |a KSP/1000066975 
020 |a 9783731506447 
024 7 |a 10.5445/KSP/1000066975  |c doi 
041 0 |a German 
042 |a dc 
100 1 |a Münch, David  |4 auth 
245 1 0 |a Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information 
260 |b KIT Scientific Publishing  |c 2017 
300 |a 1 electronic resource (XVII, 241 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism of FMTHL and SGTs to deal with erroneous, missing, and noisy data and complexity, demonstrates the robustness of situational recognition in natural scenarios, and expands generic applicability beyond discourse boundaries. 
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546 |a German 
653 |a situation recognition 
653 |a Kognitives Sichtsystem 
653 |a Situationsanalyse 
653 |a cognitive vision system 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/41905  |7 0  |z DOAB: description of the publication