ITI-CERTH participation in TRECVID 2017
Creators
- 1. Information Technologies Institute/Centre for Research and Technology Hellas
- 2. Queen Mary University of London
Description
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.
Files
trecvid2017.pdf
Files
(4.7 MB)
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Additional details
Funding
- beAWARE – Enhancing decision support and management services in extreme weather climate events 700475
- European Commission
- TENSOR – Retrieval and Analysis of Heterogeneous Online Content for Terrorist Activity Recognition 700024
- European Commission
- InVID – In Video Veritas – Verification of Social Media Video Content for the News Industry 687786
- European Commission
- EMMA – Enriching Market solutions for content Management and publishing with state of the art multimedia Analysis techniques 732665
- European Commission