| 研究生: |
謝明逢 Ming-Feng Hsieh |
|---|---|
| 論文名稱: |
利用雙攝影機取像模組建構一大型環境 Construction of a surveillance system for large monitoring spaces by a dual-camera module |
| 指導教授: |
范國清
Kuo-Chin Fan |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
資訊電機學院 - 資訊工程學系 Department of Computer Science & Information Engineering |
| 畢業學年度: | 93 |
| 語文別: | 中文 |
| 論文頁數: | 85 |
| 中文關鍵詞: | 特徵點對應 、視訊監控 |
| 外文關鍵詞: | feature point correspondences, Video Surveillance |
| 相關次數: | 點閱:10 下載:0 |
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現行單一固定式攝影機放置門口、走道或戶外街頭角落等重要位置,監視錄影環境的一舉一動,但由於監視環境空間太大,拍攝目標影像太小,碰到犯罪行為發生時,僅能拍攝到嫌疑犯的身軀,無法提供清晰影像。現行具有PTZ功能之攝影機,雖具有旋轉與放大影像功能,但僅能追蹤某一特定目標物。而吸附式之360度環場攝影機雖可監控追蹤整個環境的目標物,而後驅使PTZ攝影機取得清晰影像,但在某些開放空間場合,不易架設,如:旅館大廳、室外停車場。
基於上述的理由,本研究設計一雙攝影機取像裝置,結合兩種不同功用之攝影機,一為場景攝影機,用來監控整個環境,追蹤所有的目標物,另一為目標物攝影機,具旋轉、放大功能,用來取得目標物之清晰影像。藉由兩支攝影機之擺設位置,與利用特徵點共線之限制條件,設計一演算法,求得雙攝影機影像之對應關係。無需求得目標物在三度空間之位置,也不需事先得知攝影機的參數,直接利用影像處理的技術,自動求得系統兩台攝影機運作所需要的參數,可對多目標物追蹤,同時可取得清晰之目標物特寫鏡頭,並利用所取得之目標物特寫鏡頭,改進追蹤效果。實驗結果證明了本研究所提出之雙攝影機取像裝置是可以用來取得大環境中小目標之清晰影像。
In traditional surveillance systems, a single CCD camera is installed at the entrance of open space. The problem is that moving targets will be too small to be grabbed so that clearer and recognizable images can not be obtained for identification. As to the CCD camera with panning, tiling, and zooming (PTZ) functions, it can only track one single target.
In this thesis, a dual-camera device is designed to solve the aforementioned problems. Two cameras are installed together for different purposes. One camera called ''sense camera'' is used to monitor the whole space and to track multiple targets. The other one called ''object camera'' with PTZ functions is used to grab high quality object images. Using some geometrical properties, the two cameras can be automatically calibrated by point correspondence. Without knowing the 3D locations of objects and the camera parameters, the dual-camera device can not only track multiple targets but also obtain their high quality images in the widespreading open spaces. The tracking process can be easily switched from one target to another when multiple objects appear in the monitoring space. In addition, the tracking performance is also improved by using the detail image information grabbed from the object camera. Experiments were conducted on a wide variety of scenes and the experimental results reveal the validity of our proposed approach.
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