Content-Based Visual Summarization for Image Collections

Xingjia Pan, Fan Tang, Weiming Dong, Chongyang Ma, Yiping Meng, Feiyue Huang, Tong Yee Lee, Changsheng Xu

研究成果: Article同行評審

摘要

With the surge of images in the information era, people demand an effective and accurate way to access meaningful visual information. Accordingly, effective and accurate communication of information has become indispensable. In this article, we propose a content-based approach that automatically generates a clear and informative visual summarization based on design principles and cognitive psychology to represent image collections. We first introduce a novel method to make representative and nonredundant summarizations of image collections, thereby ensuring data cleanliness and emphasizing important information. Then, we propose a tree-based algorithm with a two-step optimization strategy to generate the final layout that operates as follows: (1) an initial layout is created by constructing a tree randomly based on the grouping results of the input image set; (2) the layout is refined through a coarse adjustment in a greedy manner, followed by gradient back propagation drawing on the training procedure of neural networks. We demonstrate the usefulness and effectiveness of our method via extensive experimental results and user studies. Our visual summarization algorithm can precisely and efficiently capture the main content of image collections better than alternative methods or commercial tools.

原文English
文章編號8880504
頁(從 - 到)2298-2312
頁數15
期刊IEEE Transactions on Visualization and Computer Graphics
27
發行號4
DOIs
出版狀態Published - 2021 四月 1

All Science Journal Classification (ASJC) codes

  • 軟體
  • 訊號處理
  • 電腦視覺和模式識別
  • 電腦繪圖與電腦輔助設計

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