Occlusion-Preserved Surveillance Video Synopsis with Flexible Object Graph.
Saved in:
| Title: | Occlusion-Preserved Surveillance Video Synopsis with Flexible Object Graph. |
|---|---|
| Authors: | Nie, Yongwei1 (AUTHOR), Ge, Wei1 (AUTHOR), Zeng, Siming1 (AUTHOR), Zhang, Qing2 (AUTHOR), Li, Guiqing1 (AUTHOR), Li, Ping3,4 (AUTHOR), Cai, Hongmin1,5 (AUTHOR) hmcai@scut.edu.cn |
| Source: | International Journal of Computer Vision. May2025, Vol. 133 Issue 5, p2653-2669. 17p. |
| Subjects: | Video summarization, Data structures, Artificial intelligence, Video surveillance, Flexible structures |
| Abstract: | Video synopsis is a technique that condenses a long surveillance video to a short summary. It faces challenges to process objects originally occluding each other in the source video. Previous approaches either treat occlusion objects as a single object, which however reduce compression ratio; or have to separate occlusion objects individually, but destroy interactions between them and yield visual artifacts. This paper presents a novel data structure called Flexible Object Graph (FOG) to handle original occlusions. Our FOG-based video synopsis approach can manipulate each object flexibly while preserving the original occlusions between them, achieving high synopsis ratio while maintaining interactions of objects. A challenging issue that comes with the introduction of FOG is that FOG may contain circulations that yield conflicts. We solve this problem by proposing a circulation conflict resolving algorithm. Furthermore, video synopsis methods usually minimize a multi-objective energy function. Previous approaches optimize the multiple objectives simultaneously which needs to strike a balance between them. Instead, we propose a stepwise optimization strategy consuming less running time while producing higher quality. Experiments demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Computer Vision is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Video synopsis is a technique that condenses a long surveillance video to a short summary. It faces challenges to process objects originally occluding each other in the source video. Previous approaches either treat occlusion objects as a single object, which however reduce compression ratio; or have to separate occlusion objects individually, but destroy interactions between them and yield visual artifacts. This paper presents a novel data structure called Flexible Object Graph (FOG) to handle original occlusions. Our FOG-based video synopsis approach can manipulate each object flexibly while preserving the original occlusions between them, achieving high synopsis ratio while maintaining interactions of objects. A challenging issue that comes with the introduction of FOG is that FOG may contain circulations that yield conflicts. We solve this problem by proposing a circulation conflict resolving algorithm. Furthermore, video synopsis methods usually minimize a multi-objective energy function. Previous approaches optimize the multiple objectives simultaneously which needs to strike a balance between them. Instead, we propose a stepwise optimization strategy consuming less running time while producing higher quality. Experiments demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 09205691 |
| DOI: | 10.1007/s11263-024-02302-5 |
