https://scholars.lib.ntu.edu.tw/handle/123456789/500597
標題: | Target-driven video summarization in a camera network | 作者: | Chen, S.-C. Lin, K. Lin, S.-Y. Chen, K.-W. Lin, C.-W. CHU-SONG CHEN YI-PING HUNG |
關鍵字: | camera network; object classification; video summarization; video surveillance | 公開日期: | 2013 | 起(迄)頁: | 3577-3581 | 來源出版物: | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings | 摘要: | Nowadays, ever expanding camera network makes it difficult to find the suspect from lengthy video records. This paper proposes a target-driven video summarization framework which provides two-step Filtered Summarized Video (FSV) for tracing suspects. Before the target is identified, users can find the target efficiently using the firststep FSV of any arbitrary camera. The first-step FSV filters all the attributes of the target including the time information and the target's categories. After identifying the target, the second-step FSV with additional spatio-temporal & appearance cues are triggered in the neighbor cameras. To enhance the accuracy of the object classification for FSV, we propose a Perspective Dependent Model (PDM) which consists of many grid-based models. Finally, the experimental results show that grid-based model is more robust than general detectors and the user study demonstrates better performance for target finding and tracking in camera network for surveillance. © 2013 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/500597 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897818218&doi=10.1109%2fICIP.2013.6738738&partnerID=40&md5=75a269bfc08c9f1bfc432d125d6de6fc |
DOI: | 10.1109/ICIP.2013.6738738 | SDG/關鍵字: | Cameras; Video recording; Camera network; Grid based models; Object classification; Spatio temporal; Target finding; Time information; Video summarization; Video surveillance; Security systems |
顯示於: | 電機工程學系 |
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