槍枝的影像辨識與資訊安全的議題已被討論許久，若能有效的從監視畫面中自動偵測到持槍歹徒，對於社會的治安維護能夠有相當大的助益，也能保障一般市民的人身安全。
槍體本身含有的特徵紋理包含外型與體積兩類，而這兩種特徵在一般背景之下較為常見，其餘的特徵則皆不明顯，所以在一般背景很難辨識出槍的存在。
本論文提出一個槍手偵測的系統，使用深度資訊為基礎，能夠在不受其背景複雜度或光影變化影響的情況下，有效的過濾背景，從而取出前景物件。再以手部持槍的方式結合槍與手兩者的外型作為特徵分類的訓練，在辨識過程中先找出手部等端點部位，並利用之前訓練好的分類器辨識使否持槍，達到偵測槍手的目的。

The issues of guns image recognition and information security have been discussed for a long time. It will help the society security, that if it detects gunmen effectively from the monitor screen. And it can protect the personal safety of the general public.
Gun body contains characteristics of square shape and small, however these characteristics are more common than the remaining ones in the general context. Therefore it is difficult to discriminate whether the gunmen exist or not in the general context.
This thesis presents a gunman detection system. It uses the depth coding so that it cannot be affected by the background complexity or brightness variation. And it also can filter characteristics effectively in the background, thereby getting the foreground object. Then we train a classifier by using the features of gun-holding-hand to combine both appearance characteristics and discriminate whether armed or not in the parts of endpoints like hand endpoint.

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