摘要
近年来,基于信息融合理论的步态识别已成为生物特征识别领域最为活跃的研究方向之一。从特征级融合和决策级融合两种层次,多特征融合、多模态融合以及多视角融合3个方面对融合理论在步态识别中的应用进行了综述。进一步,为了研究融合理论对步态识别算法性能的影响,提出一种融合了静态形体特征和动态模型特征的步态识别算法。通过在CMU步态数据库上的详细实验比较和分析,研究了不同融合策略以及步速变化对步态识别算法性能的影响。
Recently,fusion-based gait recognition has become one of the hottest topics in the domain of biometrics reco-gnition.This paper firstly discussed two different levels of fusion methods,feature-level fusion and decision-level fusion,then summarized the latest fusion-based gait recognition methods from three categories：multi-feature fusion,multi-biometric fusion and multi-view fusion.Furthermore,a gait recognition method via fusing shape and kinematics features was proposed to verify the effectiveness of fusion.Experimental results on CMU databases demonstrate the feasibility of the proposed algorithm and show that fusion can be an effective strategy to improve the recognition perfor-mance.
出处
《计算机科学》
CSCD
北大核心
2012年第12期272-277,共6页
Computer Science
基金
中财121人才工程青年博士发展基金项目(QBJGL201005)
中央财经大学科研创新团队支持计划
北京市教育共建项目资助
关键词
步态识别
多特征融合
多模态融合
多视角融合
Gait recognition
Multi-feature fusion
Multi-biometric fusion
Multi-view fusion
