Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event Retrieval Article Swipe
Vo Van Thinh
,
Nguyen Minh Khoi
,
Tran Minh Huy
,
Nguyen-Tran, Anh-Quan
,
Nguyen Duy Tan
,
Nguyen Khanh Loi
,
Phan, Anh-Minh
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2512.06334
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2512.06334
Multimedia information retrieval from videos remains a challenging problem. While recent systems have advanced multimodal search through semantic, object, and OCR queries - and can retrieve temporally consecutive scenes - they often rely on a single query modality for an entire sequence, limiting robustness in complex temporal contexts. To overcome this, we propose a cross-modal temporal event retrieval framework that enables different query modalities to describe distinct scenes within a sequence. To determine decision thresholds for scene transition and slide change adaptively, we build Kernel Density Gaussian Mixture Thresholding (KDE-GMM) algorithm, ensuring optimal keyframe selection. These extracted keyframes act as compact, high-quality visual exemplars that retain each segment's semantic essence, improving retrieval precision and efficiency. Additionally, the system incorporates a large language model (LLM) to refine and expand user queries, enhancing overall retrieval performance. The proposed system's effectiveness and robustness were demonstrated through its strong results in the Ho Chi Minh AI Challenge 2025.
Related Topics
Concepts
Computer science
Robustness (evolution)
Video retrieval
Artificial intelligence
Query expansion
Thresholding
Visual Word
Image retrieval
Information retrieval
Kernel density estimation
Event (particle physics)
Limiting
Mixture model
Search engine indexing
Modalities
Query language
Discriminative model
Relevance feedback
Kernel (algebra)
Visualization
Modality (human–computer interaction)
Pattern recognition (psychology)
Sliding window protocol
Computer vision
Histogram
Machine learning
Metadata
- Type
- preprint
- Landing Page
- https://doi.org/10.48550/arxiv.2512.06334
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7111372480
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7111372480Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2512.06334Digital Object Identifier
- Title
-
Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event RetrievalWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-06Full publication date if available
- Authors
-
Vo Van Thinh, Nguyen Minh Khoi, Tran Minh Huy, Nguyen-Tran, Anh-Quan, Nguyen Duy Tan, Nguyen Khanh Loi, Phan, Anh-MinhList of authors in order
- Landing page
-
https://doi.org/10.48550/arxiv.2512.06334Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.48550/arxiv.2512.06334Direct OA link when available
- Concepts
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Computer science, Robustness (evolution), Video retrieval, Artificial intelligence, Query expansion, Thresholding, Visual Word, Image retrieval, Information retrieval, Kernel density estimation, Event (particle physics), Limiting, Mixture model, Search engine indexing, Modalities, Query language, Discriminative model, Relevance feedback, Kernel (algebra), Visualization, Modality (human–computer interaction), Pattern recognition (psychology), Sliding window protocol, Computer vision, Histogram, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
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| abstract_inverted_index.selection. | 94 |
| abstract_inverted_index.temporally | 26 |
| abstract_inverted_index.thresholds | 74 |
| abstract_inverted_index.transition | 77 |
| abstract_inverted_index.adaptively, | 81 |
| abstract_inverted_index.challenging | 7 |
| abstract_inverted_index.consecutive | 27 |
| abstract_inverted_index.cross-modal | 54 |
| abstract_inverted_index.efficiency. | 114 |
| abstract_inverted_index.information | 1 |
| abstract_inverted_index.Thresholding | 88 |
| abstract_inverted_index.demonstrated | 141 |
| abstract_inverted_index.high-quality | 101 |
| abstract_inverted_index.incorporates | 118 |
| abstract_inverted_index.performance. | 133 |
| abstract_inverted_index.Additionally, | 115 |
| abstract_inverted_index.effectiveness | 137 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |