研究生: |
簡翊峰 I-Feng Chien |
---|---|
論文名稱: |
基於空間時序網路的異常事件偵測 Spatio-Temporal Networks for Abnormal Event Detection |
指導教授: |
花凱龍
Kai-Lung Hua |
口試委員: |
花凱龍
Kai-Lung Hua 陳永耀 Yung-Yao Chen 楊朝龍 Chao-Lung Yang 陸敬互 Ching-Hu Lu 簡士哲 Shih-Che Chien |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 英文 |
論文頁數: | 32 |
中文關鍵詞: | 空間時序網路 、異常事件偵測 |
外文關鍵詞: | spatio-temporal network, abnormal event detection |
相關次數: | 點閱:134 下載:0 |
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異常事件可能造成經濟損失與人員傷亡,能夠在提早偵測出這些異常事件是
避免重大損失的唯一方法。在我們的論文中,我們提出了一種使用攝像機的及時
偵測異常事件的方法,該方法可以工作在不同環境。異常事件通常只出現在影像
的一小塊區域,因此我們使用兩階段架構來提高準確度。在第一階段,我們使用 空間時序網路從影片中找出異常的區域,在第二階段我們使用 Resnet 判斷該區域
是否為正常狀態。我們的實驗結果證明,我們提出的方法比其他方法具有更好的
準確度。
Abnormaleventscancauseeconomiclossesandcasualties. Beingabletodetectabnormal events in the early stage is the only way to avoid significant losses. In our thesis, we present a method of using cameras to detect abnormal events in time, which can work in different environments. Abnormal events usually only appear in a small area of the image,soweuseatwostagearchitecturetoimproveaccuracy. Inthefirstphase,weuse the spatiotemporal network to find the area that might be a abnormal events from the video. Inthesecondstage,WeuseResnettodeterminewhethertheareaisnormalornot. Our experimental results show that the proposed method has better accuracy than other methods.
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