本研究期望建立一套校正邏輯作為指向影像辨識系統之調整機制，使得機器視覺對於指向延伸向量之邏輯能夠與使用者瞄準落點相符合。研究方法是透過指向瞄準動作的表達來找出指向向量在目標平面上之落點分布以及探討其背後瞄準策略以及關節位置之差異。受試者共有10人，分別在有視覺回饋及無視覺回饋下之不同狀態下進行遠距指向瞄準動作。實驗設計是藉由VICON攝影機抓取受試者手指、手臂關節上以及雙眼感光點在空間的3D座標位置，將此資料經由程式計算。藉由觀察法找出指向落點分布分類的重要特徵。精準度分析方面期望取得兩種狀態下的目標物接收範圍之參考直徑，以尋得造成不同指向落點分布特徵表現以及不同偏誤類型之原因並探討並校正準確度。
由實驗數據輸出結果以及原因追溯可發現，指向落點分布共可分為三類：(1)擴散型 (2)左上平移型 (3)接近命中型。準度與精度方面在有視覺回饋下準度受到目標物角度與距離影響，無視覺回饋下受到目標物與螢幕中央距離影響。無視覺回饋下偏誤原因，主要來自指向向量與手眼瞄準向量間相對角度之差異大小，並與之成正比。最後，依照不同之指向落點以及分割校正區域分類降低資料離散程度進行以手眼瞄準落點為目標之複迴歸校正，校正後偏誤比較之結果，將目標紅心與指向落點原先約32.66公分的平均落差降低至平均約14.23公分的誤差，分類校正後誤差各降至(1)13.14公分(2)8.8公分(3)7.54公分。校正結果證明本研究所使用之分布分類以及區域分割，皆對校正系統之誤差降低產生進一步效果。

A logical system of adjustment was developed in the study for eye-hand coordination in goal-directed aiming and finger gesture recognition logic. This research assume the distortion between eye-hand coordination in goal-directed aiming and finger vector gesture recognition logic can be satisfactorily compensated with a 2-dimensional quadratic function. There are ten participants were recruited for the study. A total of 12 markers were attached onto the joints and fingertips of the index finger, the right arm, close to two eyes and the plane of target. Vicon Motion Analysis Systems with 8 cameras was used to record the motion of goal-directed movement and aiming in two different situation: (1)Visual feedback (2)without Visual feedback In this experiment, and each marker were generated. Then use Matlab to calculate the finger line vector end-points on the plane of target, and investigate the strategy of aiming form participants. Different size and position of target will make accuracy different in visual feedback. Different distance of target will make accuracy different without visual feedback.
Obviously, there are three types in these finger pointing distributions: (1)extend (2)Up&right-shift (3)close-to-target. According these three classification to adjust the finger line vector end-points close to the position of eye-hand coordination goal-directed aiming. Then, according the result of experiment analysis to divide the region for reduce the inaccuracy. This method can reduce the position error about 90% effectively, and reduce the accuracy error form 32.66cm to 14.23cm.Diminish the target receive region effectively.

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