Improving the Flexibility of Video Events Retrieval Through Dynamic Conditional Refinement With Multilingual Capabilities

Our paper introduces a novel middleware designed to enhance the user experience of novice users of video event retrieval systems. The middleware simplifies the search process while maintaining advanced semantic information-seeking features. It achieves this by refining sentence representation, rewriting the original query based on user intent and dataset metadata knowledge, reducing ambiguities, and increasing relevance with domain-specific terms. Our approach allows users to provide simplified descriptions, while the system automates query refinement and parameterizes these for different search functions. This reduces the difficulty of navigating complex user interfaces and selecting from available functionalities. Additionally, the multilingual feature supports non-native English speakers by helping them describe their queries more effectively. In general, our system is suitable for people who are not experienced in advanced retrieval tasks, specifically focusing on its applicability in the special session Interactive Video Retrieval for Beginners (IVR4B).

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/cbmi62980.2024.10859202
Citations
1
Primary Topic
Video Analysis and Summarization
Type
article
Field-Weighted Citation Impact
0.25
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article

Improving the Flexibility of Video Events Retrieval Through Dynamic Conditional Refinement With Multilingual Capabilities

Cathal Gurrin, Van-Tu Ninh, Thang-Long Nguyen-Ho, Graham Healy et al.
1 citations
Video Analysis and Summarization
0.25
article

Improving the Flexibility of Video Events Retrieval Through Dynamic Conditional Refinement With Multilingual Capabilities

Cathal Gurrin, Van-Tu Ninh, Thang-Long Nguyen-Ho, Graham Healy, Minh–Triet Tran
article en
1 citations

Abstract

Our paper introduces a novel middleware designed to enhance the user experience of novice users of video event retrieval systems. The middleware simplifies the search process while maintaining advanced semantic information-seeking features. It achieves this by refining sentence representation, rewriting the original query based on user intent and dataset metadata knowledge, reducing ambiguities, and increasing relevance with domain-specific terms. Our approach allows users to provide simplified descriptions, while the system automates query refinement and parameterizes these for different search functions. This reduces the difficulty of navigating complex user interfaces and selecting from available functionalities. Additionally, the multilingual feature supports non-native English speakers by helping them describe their queries more effectively. In general, our system is suitable for people who are not experienced in advanced retrieval tasks, specifically focusing on its applicability in the special session Interactive Video Retrieval for Beginners (IVR4B).

Vietnam National University Ho Chi Minh City (VN), Dublin City University (IE)
Openalex Percentile: Top 42%
Video Analysis and Summarization
0.25
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Improving the Flexibility of Video Events Retrieval Through Dynamic Conditional Refinement With Multilingual Capabilities — Cathal Gurrin, Van-Tu Ninh, et al. · (2024) | TGRS Research Map | TGRS