摘要
对于只有单一步态信息的特征数据库,在人数众多时,遍历识别算法识别时间长、识别率低.针对这个缺点,提出一种结构化步态特征表征和快速步态识别方法,将人的步态信息与身高、性别、年龄等一起构成结构化的步态特征,用不同传感器采集数据,不同的方法提取各个特征分量并独立加以利用.结构化的步态特征便于识别算法对步态识别问题进行分级处理,缩小识别范围.实验表明,文中方法不仅能够提高识别速度,而且能获得更高的识别率.
When the gait database contains the only gait feature, the larger the number of individuals is, the longer time the recognition algorithm costs and the lower the recognition ratio is. Aiming at this problem, a structured gait feature expression and fast gait recognition method is presented. The structured gait feature are made up of gait information, individual height, sex, age and other information. These feature components are sampled by different sensors and used independently. The proposed gait recognition algorithm utilizes the structured feature to deal with the gait recognition hierarchically. The large identification range is narrowed. The experimental results demonstrate that the proposed method improves the recognition speed and gains higher identification precision.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2012年第2期248-255,共8页
Pattern Recognition and Artificial Intelligence
关键词
分级步态识别
结构化步态特征
多传感器数据采集
Hierarchical Gait Recognition, Structured Gait Feature, Sampling with Multiple Sensors
