10.5281/zenodo.1183440
https://zenodo.org/records/1183440
oai:zenodo.org:1183440
Markatopoulou, Foteini
Foteini
Markatopoulou
Information Technologies Institute/Centre for Research and Technology Hellas
Moumtzidou, Anastasia
Anastasia
Moumtzidou
Information Technologies Institute/Centre for Research and Technology Hellas
Galanopoulos, Damianos
Damianos
Galanopoulos
Information Technologies Institute/Centre for Research and Technology Hellas
Avgerinakis, Konstantinos
Konstantinos
Avgerinakis
Information Technologies Institute/Centre for Research and Technology Hellas
Andreadis, Stelios
Stelios
Andreadis
Information Technologies Institute/Centre for Research and Technology Hellas
Gialampoukidis, Ilias
Ilias
Gialampoukidis
Information Technologies Institute/Centre for Research and Technology Hellas
Tachos, Stavros
Stavros
Tachos
Information Technologies Institute/Centre for Research and Technology Hellas
Vrochidis, Stefanos
Stefanos
Vrochidis
Information Technologies Institute/Centre for Research and Technology Hellas
Mezaris, Vasileios
Vasileios
Mezaris
Information Technologies Institute/Centre for Research and Technology Hellas
Kompatsiaris, Ioannis
Ioannis
Kompatsiaris
Information Technologies Institute/Centre for Research and Technology Hellas
Patras, Ioannis
Ioannis
Patras
Queen Mary University of London
ITI-CERTH participation in TRECVID 2017
Zenodo
2018
2018-02-23
10.5281/zenodo.1183439
https://zenodo.org/communities/invid-h2020
https://zenodo.org/communities/emma-h2020
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
This paper provides an overview of the runs submitted to TRECVID 2017 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 with concept-based and semantic-embedding representations of video fragments. Regarding the MED task, this year we participate on Pre-Specied and Ah-Hoc sub-tasks exploiting both motion-based as well as DCNN-based features. The INS task is performed by employing VERGE, which is an interactive retrieval application that integrates retrieval functionalities that consider mainly visual information. For the SED task, we deploy a novel activity detection algorithm that is based on human detection in video frames, goal descriptors, dense trajectories, Fisher vectors and a discriminative action segmentation scheme.
European Commission
10.13039/501100000780
700475
Enhancing decision support and management services in extreme weather climate events
European Commission
10.13039/501100000780
700024
Retrieval and Analysis of Heterogeneous Online Content for Terrorist Activity Recognition
European Commission
10.13039/501100000780
687786
In Video Veritas – Verification of Social Media Video Content for the News Industry
European Commission
10.13039/501100000780
732665
Enriching Market solutions for content Management and publishing with state of the art multimedia Analysis techniques