تقرير
Cluster-based Video Summarization with Temporal Context Awareness
| العنوان: | Cluster-based Video Summarization with Temporal Context Awareness |
|---|---|
| المؤلفون: | Huynh-Lam, Hai-Dang, Ho-Thi, Ngoc-Phuong, Tran, Minh-Triet, Le, Trung-Nghia |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
| الوصف: | In this paper, we present TAC-SUM, a novel and efficient training-free approach for video summarization that addresses the limitations of existing cluster-based models by incorporating temporal context. Our method partitions the input video into temporally consecutive segments with clustering information, enabling the injection of temporal awareness into the clustering process, setting it apart from prior cluster-based summarization methods. The resulting temporal-aware clusters are then utilized to compute the final summary, using simple rules for keyframe selection and frame importance scoring. Experimental results on the SumMe dataset demonstrate the effectiveness of our proposed approach, outperforming existing unsupervised methods and achieving comparable performance to state-of-the-art supervised summarization techniques. Our source code is available for reference at \url{https://github.com/hcmus-thesis-gulu/TAC-SUM}. Comment: 14 pages, 6 figures, accepted in PSIVT 2023 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1007/978-981-97-0376-0_2 |
| URL الوصول: | http://arxiv.org/abs/2404.04511 |
| رقم الأكسشن: | edsarx.2404.04511 |
| قاعدة البيانات: | arXiv |
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