Published June 12, 2023 | Version 1.0
Conference paper Open

Improving Query and Assessment Quality in Text-Based Video Retrieval Evaluation

  • 1. JOANNEUM RESEARCH
  • 2. University of Basel
  • 3. CNR ISTI
  • 4. CERTH ITI
  • 5. Reykjavik University
  • 6. Charles University, Prague
  • 7. City University Hong Kong

Description

Different task interpretations are a highly undesired element in interactive video retrieval evaluations. When a participating team focuses partially on a wrong goal, the evaluation results might become partially misleading. In this paper, we propose a process for refining known-item and open-set type queries, and preparing the assessors that judge the correctness of submissions to open-set queries. Our findings from recent years reveal that a proper methodology can lead to objective query quality improvements and subjective participant satisfaction with query clarity.

Files

Improving_Query_and_Assessment_Quality_in_Text_based_Video_Retrieval_Evaluation-1.pdf

Additional details

Funding

XRECO – XR mEdia eCOsystem 101070250
European Commission
AI4Media – A European Excellence Centre for Media, Society and Democracy 951911
European Commission