近年來以影像為基礎分析步伐姿態成為一新的研究方向，步伐姿態被認為可以作為一生物特徵來辨識人，或是反映個人身體狀況，然而，大部分有關步態的研究都以辨識人的身份為主，並且未包含異常的步伐情形。另一方面，在居家看護及監控系統上，我們需要行為分析來偵測異常的動作以期系統能做出適宜的反應。
　　考慮到上述的情況，本論文提出一套以視訊影像分析人類步伐的方法，藉由此方法可有效抓出步態的幾種特性，並依此特性分辨出幾種異常的步伐。本論文的分析方法是先以扣除背景的演算法將每張影像中人的部分分離出來，接著我們在每張影像中抓出一個以二腳距離為為基礎的特徵值，藉由觀察這個特徵值的變化，我們抓出數個描述步態特徵的量，根據這些量，幾種我們認定為異常的步態情況可以被辨認出來。

　Gait, or the style of walking, has recently been a popular topic in vision-based analysis. It is believed that gait is unique to every individual and reflects body conditions. However, current vision-based works about gait are mostly devoted to the application of human recognition, and abnormal walking styles are not included for discussion. On the other hand, behavior analysis in home care system or other surveillance application is needed for detecting unusual events so as to making proper response.
　Considering the above points, in this thesis, a vision-based method is proposed to analyze abnormal types of walking. With this analysis, a few abnormal types of walking can be distinguished. In the proposed method, a background subtraction algorithm is first applied to segment out the silhouette of the walker at each frame in a sequence. For each frame, we define a feature based on the length between two legs, called aspect ratio, and by observing this feature value across time (or frame), a periodic wave is obtained. Then, based on the quantities measured from this wave, several attributes about gait are extracted. Finally, a preliminary classification is used to determine if the style of walking in a sequence is among the abnormal types we can find.

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