[1]贲晛烨,王科俊,马慧.视频下的正面人体身份自动识别[J].智能系统学报,2012,7(01):69-74.
 BEN Xianye,WANG Kejun,MA Hui.Videobased automatic frontview human identification[J].CAAI Transactions on Intelligent Systems,2012,7(01):69-74.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第7卷
期数:
2012年01期
页码:
69-74
栏目:
出版日期:
2012-02-25

文章信息/Info

Title:
Videobased automatic frontview human identification
文章编号:
1673-4785(2012)01-0069-06
作者:
贲晛烨12王科俊3马慧34
1.山东大学 信息科学与工程学院,山东 济南 250100;
2.哈尔滨工业大学 交通科学与工程学院,黑龙江 哈尔滨 150090;
3.哈尔滨工程大学 自动化学院,黑龙江 哈尔滨 150001;
4.黑龙江大学 电子工程学院,黑龙江 哈尔滨 150086
Author(s):
BEN Xianye12 WANG Kejun3 MA Hui34
1.School of Information Science and Engineering, Shandong University, Ji’nan 250100, China;
2.School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China;
3.College of Automation, Harbin Engineering University, Harbin 150001, China;
4. School of Electronic Engineering, Heilongjiang University, Harbin 150086, China
关键词:
身份识别步态识别Adaboost人脸特征正面步态周期检测
Keywords:
human identification gait recognition Adaboost facial feature frontview gait period detection
分类号:
TP391.41
文献标志码:
A
摘要:
为了能够实现视频下正面人体身份的自动识别,设计的系统包括Adaboost行人检测、Adaboost人脸检测、肤色验证、步态预处理、周期检测、特征提取以及决策级融合识别等模块.通过行人检测模块可以自动开启人脸检测模块和步态周期检测模块.实验结果表明,提出的根据下臂摇摆区域确定步态周期的方法对正面步态周期检测准确,计算量小,适用于实时的步态识别.采用人脸特征辅助步态特征在决策级的融合方法是解决视频下身份识别的新思路,在单样本的步态识别中,融合人脸特征可以提高识别精度.
Abstract:
A system was designed to automatically identify a person from a frontview angle in a video sequence, including the modules of Adaboost pedestrian detection, Adaboost face detection, complexion verification, gait preprocessing, period detection, feature extraction, and decisionmaking level amalgamation and identification. The face detection module and gait period detection module can be activated automatically by the pedestrian detection module. The experimental results show that the swinging arm region can be detected for obtaining the frontview gait period accurately with minimal computation, which is suitable for realtime gait recognition. Applying gait features assisted by face features to the decisionmaking level amalgamation method to solve human identification in a video sequence is a new idea. Even in gait recognition with a single sample per person, this proposed scheme can achieve an improvement in the correct recognition rate when face and gait information are integrated as opposed to using gait features alone. 

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备注/Memo

备注/Memo:
收稿日期: 2010-09-09.
网络出版时间: 2012-02-16.
基金项目:国家自然科学基金资助项目(61105057);中国博士后科学基金面上资助项目(20110491087). 
通信作者:贲晛烨.         E-mail:benxianyeye@163.com.
作者简介:
贲晛烨,女,1983年生,讲师,主要研究方向为模式识别、度量学习、超分辨率人脸识别、步态识别.申请专利5项,已授权4项,发表学术论文30余篇,其中18篇被EI检索.
王科俊,男,1962年生,教授,博士生导师,博士,哈尔滨工程大学模式识别与智能系统学科带头人.主要研究方向为模糊混沌神经网络、自适应逆控制理论、可拓控制、网络智能控制、模式识别、多模态生物特征识别、联脱机指纹考试身份鉴别系统、微小型机器人系统等.完成科研项目20余项,目前在研项目10余项.曾获得部级科技进步二等奖2项、三等奖3项,省高校科学技术一等奖1项、二等奖1项.获发明专利1项,公开3项,国家版权局软件著作权登记1项. 发表学术论文180余篇,出版学术专著3部、国防教材1部,主审教材2部. 
 马慧,女,1982年生,讲师,主要研究方向为模式识别、图像处理、生物特征识别.申请专利3项,发表学术论文5篇,其中4篇被EI检索.
更新日期/Last Update: 2012-05-07