论文标题
使用单词袋特征表示方法的人体步态识别
Human Gait Recognition Using Bag of Words Feature Representation Method
论文作者
论文摘要
在本文中，我们提出了一种基于单词特征表示方法的新型步态识别方法。该算法对独特的人类步态数据进行了训练，测试和评估，该数据由93个个体组成，他们在两个不同的课程中以两个端点之间的舒适步伐行走。为了评估提出模型的有效性，将结果与使用提取的特征进行分类的输出进行了比较。在提出的情况下，与使用常见的统计特征相比，所提出的方法在所有使用的分类器中都可以显着提高准确性。
In this paper, we propose a novel gait recognition method based on a bag-of-words feature representation method. The algorithm is trained, tested and evaluated on a unique human gait data consisting of 93 individuals who walked with comfortable pace between two end points during two different sessions. To evaluate the effectiveness of the proposed model, the results are compared with the outputs of the classification using extracted features. As it is presented, the proposed method results in significant improvement accuracy compared to using common statistical features, in all the used classifiers.
