• 多媒体技术及应用 •

### 一种基于线性序列差异分析降维的人体行为识别方法

1. 江南大学 物联网工程学院,江苏 无锡 214122
• 收稿日期:2018-01-18 出版日期:2019-03-15 发布日期:2019-03-15
• 作者简介:鹿天然(1993—),女,硕士研究生,主研方向为模式识别、智能系统;于凤芹、陈莹,教授、博士。
• 基金项目:

国家自然科学基金(61573168);中央高校基本科研业务费专项资金(JUSRP51733B)。

### A Human Action Recognition Method Based on LSDA Dimension Reduction

LU Tianran,YU Fengqin,CHEN Ying

1. School of Internet of Things Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China
• Received:2018-01-18 Online:2019-03-15 Published:2019-03-15

Abstract:

Aiming at the problem that dimensionality disaster easily occurs in the processing of dealing with video data,a dimension reduction method called Linear Sequence Discriminant Analysis(LSDA) is proposed for human action recognition.ViBe algorithm is used to subtract the backgrounds of video frames to get action areas,and dense trajectories are extracted in these areas to suppress the noise caused by camera movements.Fisher Vector is used to encode the features and linear sequence discriminant analysis is conducted on them,the sequence class separability is measured by dynamic time warping distance.In order to reduce the data dimension,a linear discriminative projection of the feature vectors in sequences is mapped to a lower-dimensional subspace by maximizing the between-class separability and minimizing the within-class separability.Support Vector Machine(SVM) is learned from the reduced dimension features,and then get the results of human action recognition.Simulation results on KTH datasets and UCF101 datasets show that compared with Principal Component Analysis(PCA),Linear Discriminant Analysis(LDA) and other dimension reduction methods,the proposed method can effectively improve the recognition accuracy.