本論文的主要目標為建立一個立體視覺系統以估測目標點與攝影機的距離。單張影像無法提供確切的深度資訊，必須藉由多張影像已達成此目的。在立體視覺中尋找對應點是非常重要的。一般尋找對應點會針對固定目標點的特色做處理，例如：顏色、形狀等，但是如果有這樣的限制，立體測距將會被特定的目標點限制，而降低其實用性。
本論文可以分為三大步驟，第一步驟利用兩個一般的網路攝影機擷取畫面，由於我們必須解決徑向扭曲和雙攝影機光軸不平行的問題，因此需要做影像校正。第二步驟依據目標點附近的紋理選擇尋找對應點的方法，若目標點附近紋理豐富，則利用紋理使用絕對差值總和演算法，若相反，則利用顏色分佈使用自動調整樣版大小均值移動演算法。第三步驟利用三角成像原理，計算出目標點與攝影機之間的距離。
在我們的實驗結果中顯示當我們對影像校正做進一步的修改後，我們可以利用低價位的攝影機，和依據目標點的特性來估測其距離，並且擁有不錯的準確度其最大平均誤差在3.04%以內。

The purpose of this thesis is to build a stereo vision system for estimating distances between the target point and the webcams. We construct the stereo system in order to estimate exact information of depth by locating the corresponding points. In general, locating the corresponding point is achieved by the features of the object, such as color and shape. However, the selection of target points will be limited and the adaptability of the system will be declined. Thus, the method was proposed to locate the corresponding point according to the texture around the target point.
This system consists of three major steps. First, Images are captured by two webcams. The image calibration is needed in order to get the parameters of the webcams, to deal with the distortion, and to compensate the unparalleled optical axes. Second, two different ways are used to find the corresponding point according to the texture around the target point. If the texture around the target point is complex, we use the Sum of Absolute Difference algorithm to find the corresponding point. Otherwise, the Adaptive Bandwidth Mean Shift algorithm is used. Finally, by the triangular perspective projection, the distance between the target point and webcams can be estimated.
After the proposed image calibration algorithm, the system can be implemented with low-price cameras. The experimental results show that the accuracy is well with mean error rate less than 3.04%.

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