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

Beteiligte Autor*innen der JOANNEUM RESEARCH:
Autor*innen:
Bailer, Werner and Arnold, Rahel and Benz, Vera and Coccomini, Davide and Gkagkas, Anastasios and Guðmundsson, Gylfi Þór and Heller, Silvan and Jónsson, Bjoern Þór and Lokoc, Jakub and Messina, Nicola and Pantelidis, Nick and Wu, Jiaxin
Abstract:
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 knownitem and openset type queries, and preparing the assessors that judge the correctness of submissions to openset 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.
Titel:
Improving Query and Assessment Quality in Text-Based Interactive Video Retrieval Evaluation
Herausgeber (Verlag):
ACM

Publikationsreihe

Buchtitel
Proceedings of the 2023 ACM International Conference on Multimedia Retrieval
Herausgeber(Verlag)
ACM

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