Conference paper Open Access

ITI-CERTH participation in TRECVID 2016

Foteini Markatopoulou; Anastasia Moumtzidou; Damianos Galanopoulos; Theodoros Mironidis; Vagia Kaltsa; Anastasia Ioannidou; Spyridon Symeonidis; Konstantinos Avgerinakis; Stelios Andreadis; Ilias Gialampoukidis; Stefanos Vrochidis; Alexia Briassouli; Vasileios Mezaris; Ioannis Kompatsiaris; Ioannis Patras


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    <dct:title>ITI-CERTH participation in TRECVID 2016</dct:title>
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    <dcat:keyword>Multimedia Event Detection (MED)</dcat:keyword>
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    <dcat:keyword>Surveillance Event Detection (SED)</dcat:keyword>
    <dcat:keyword>Kernel Kub class Discriminant Analysis method (KSDA)</dcat:keyword>
    <dcat:keyword>Motion Boundary Activity Areas (MBAA)</dcat:keyword>
    <dcat:keyword>VERGE</dcat:keyword>
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    <dct:description>&lt;p&gt;This paper provides an overview of the runs submitted to TRECVID 2016 by ITI-CERTH. ITI-CERTH participated in the Ad-hoc Video Search (AVS), Multimedia Event Detection (MED), Instance Search (INS) and Surveillance Event Detection (SED) tasks. Our AVS task participation is based on a method that combines the linguistic analysis of the query and the concept-based annotation of video fragments. In the MED task, in 000Ex task we exploit the textual description of an event class in order retrieve related videos, without using positive samples. Furthermore, in 010Ex and 100Ex tasks, a kernel sub class version of our discriminant analysis method (KSDA) combined with a fast linear SVM is employed. The INS task is performed by employing VERGE, which is an interactive retrieval application that integrates retrieval functionalities that consider only visual information. For the SED task, we deploy a novel activity detection algorithm that is based on Motion Boundary Activity Areas (MBAA), dense trajectories, Fisher vectors and an overlapping sliding window.&lt;/p&gt;</dct:description>
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