本文使用逆向歪斜光線追蹤方法，建立新的相機校正方法，藉由相機取得影像而求得待測物位置，以歪斜光線追蹤對相機做參數校正，以提高相機系統之性能，進而應用在移動物的偵測技術上。

　　相機之參數校正為移動物偵測中一重要環節，參數校正是否準確對相機系統的性能甚大。目前現有之相機參數校正方法甚多，但所有方法都是以針孔模型為基礎而發展，但針孔成像模型只是一種以透視投影法的近似方法，並不符合幾何光學Snell定理，因此使用現有參數校正方法是不可能使相機系統的性能更臻完美。本文中使用了歪斜光線追蹤的方法，藉由真正的幾何尺寸來建立起物體與像之間幾何關係，進而校正照相機的5個內部參數、4個外部參數及 個元件位置參數，得到影像平面與物點世界座標系之間正確的幾何關係，使歪斜光線追蹤結果更準確，也可消除像差在移動物偵物的影響，以提高移動物偵物之精確度。

　This paper presents a new camera calibration method by using skew ray tracing. Instead of pinhole model, the parameters of this system are calibrated by using skew ray tracing method based on Snell’s law, and it can apply on motion detection.

　Camera calibration is a crucial problem for motion detection. However, all existing methods of camera calibration are developed based on pinhole model, an approximation algorithm against to Snell’s law. Thus, it is impossible to obtain an accurate method of camera calibration by using a mathematical pinhole model. Using full modeling of lens geometry, the proposed method establishes the geometric relationship between images and objects via Snell's Law. This paper models the geometric relationship between 2-D images and 3-D world by using skew ray tracing theory to calibrate five intrinsic parameters, five extrinsic parameters and pose parameters of elements. This method can avoid the influence of the aberration by getting the virtual image in object side. It can minimum the noise and increase the recognition of detection system.

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