Graph-Based Embedding Improvement Feature Distribution in Videos

Junbin Zhang, Pei-Hsuan Tsai, Meng Hsun Tsai

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Video understanding is a significant computer vision research subject since online video content is growing exponentially. Feature extraction and representation play a crucial role in video understanding tasks such as classification, segmentation, and recognition. However, the model's learning is ambiguous since adjacent video frames typically have similar RGB features. To address this issue, we present graph-based embedding to enhance video feature distribution. We construct a graph-structured of videos by connecting similar features. Node embedding is generated by utilizing a graph model. Experiments demonstrate that our approach effectively improves feature distribution. The graph attention network (GAT) improves accuracy and editing score by 4% over the visual model.

原文English
主出版物標題2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面435-436
頁數2
ISBN(電子)9798350324174
DOIs
出版狀態Published - 2023
事件2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Pingtung, Taiwan
持續時間: 2023 7月 172023 7月 19

出版系列

名字2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

Conference

Conference2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023
國家/地區Taiwan
城市Pingtung
期間23-07-1723-07-19

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 人機介面
  • 資訊系統
  • 資訊系統與管理
  • 電氣與電子工程
  • 媒體技術
  • 儀器

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