由於人們對於居家與人身財產安全的要求，視訊監控需求越來越多。但是傳 統的視訊監控設備無法即時的分析人員的身份；因此，本論文提出一種基於人的 行走姿態作為身份辨識的系統。每個人的行走姿態都是規律且獨特的，我們藉由 每個人的行走特徵來識別一個人的身份，而如何擷取行走的特徵是整個辨識系統 的成敗關鍵。本論文提出貼片式中心對稱區域三元圖樣的步態特徵擷取技術，期 望能夠在步態身份辨識能夠有較佳的辨識效能與準確性。由第四章實驗結果可以 得知，我們所提出的方法在身份鑑別上，具有不錯的效果。進一步分析本論文所 提出的方法後，我們可以得到以下的結論：
在步態身份辨識系統中，特徵擷取方法的優劣，將影響整個系統的辨識能力。
本論文提出貼片式中心對稱區域三元圖樣的步態特徵擷取技術，該技術藉由將 GEI 影像經過 TPCS-LTP 運算後，再把獲取的特徵值經由 SVM 進行分類。並從 實驗結果證實我們所提出方法對於步態身份辨識具有不錯的效能與準確性。為了 證實我們的方法能夠應用在生活中，我們實驗了穿著大衣與攜帶包包的狀態。實 驗結果也證實在物件外表有所改變時，我們所提出的方法還是有不錯的辨識效 果。
步態的身份辨識是一門很深的學問，在未來還有許多是我們需要去克服與討 論的問題。對於本論文所提出的方法，在未來我們可以把研究重點著重在以下幾 點：
1. 影像前景處理：在影像前景偵測上，我們使用背景相減法進行前景偵測，之 後可以嘗試不同的前景偵測法來進行影像的前處理。
2. 特徵提取的方法：在本論文中我們使用的是一種基於整體外觀特徵的提取方 法，在未來我們可以嘗試使用部分人體結構當特徵的方法，以此建立身份辨識所 需的特徵。
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3. 增加步態資料庫：目前使用的實驗資料庫是在步態辨識領域中，較為常見的 資料庫，如果在未來能夠增加更多的步態資料庫來測試系統效能，將可提供更客 觀的分析數據。
4. 實際應用層面：在實際生活的應用上，或許能夠結合各式軟硬體，使其應用 層面更廣，例如：監控系統、取代傳統密碼等等。
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