沈阳航空航天大学学报Issue(2)：65-69,5.DOI:10.3969/j.issn.2095-1248.2014.02.015
基于AdaBoost算法特征提取的人体动作识别方法
Human action recognition method based on AdaBoost algorithm for feature extraction
摘要
Abstract
This paper proposed a novel action recognition method based on AdaBoost algorithm. Selecting the most discriminative sample subset from a large amount of raw features of training data,the method re-duces the computational complexity of recognition with high accuracy,and realizes the swift and precise hu-man action recognition. The three-dimensional scale invariant feature transform ( 3D SIFT ) descriptor of space-time interest points is utilized to achieve raw feature data by representing the motion video sequences. In order to select the most discriminative samples,AdaBoost algorithm is applied to the raw feature data. The nearest neighbor classifier algorithm is used to test the proposed method on the KTH database. Experiment results show that the method not only achieves the better recognition rate,but also greatly improves the speed of recognition. The validity of the proposed method is proved.关键词
人体动作识别/时空兴趣点/AdaBoost算法/最近邻分类器Key words
human action recognition/space-time interest points/AdaBoost algorithm/nearest neighbor clas-分类
信息技术与安全科学引用本文复制引用
姬晓飞,周路,李一波..基于AdaBoost算法特征提取的人体动作识别方法[J].沈阳航空航天大学学报,2014,(2):65-69,5.基金项目
国家自然科学基金(项目编号:61103123) （项目编号:61103123）
教育部留学回国人员启动基金资助。 （）
