期刊刊名：修平學報 　 卷期：23期

篇名出版日期：2011年9月1日

作者：Meng-Fen Ho,Chung-Lin Huang,何孟芬,黃仲陵

語言：English

關鍵字：Gait analysis, human identification,步伐姿態分析,人物辨識

被點閱次數：14次

閱讀時間：604sec

摘要：
In this paper, we propose a gait analysis method to extract the dynamic and static information from the input video for walking path determination and human identification. Based on the periodicity of swing distances, we may estimate the gait period of each walking video sequence. For each gait cycle, we depict the dynamic information by analyzing the distribution of motion vectors, and then describe the static information by using Fourier descriptors. The extracted dynamic and static information is transformed into lower dimensional embedding space for human identity recognition. To solve the difference of walking velocity between the test and training human objects, a hybrid human ID recognition algorithm is developed to choose the effective feature. Given a test feature vector, the nearest neighbor classifier is applied for walking paths determination and human identification. The proposed algorithm is evaluated on the CASIA gait database, and the experimental results demonstrate a highly acceptable recognition rate, for example, 98% for normal walking dataset.

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