Gait Based Human Recognition with Various Classifiers Using Exhaustive Angle Calculations in Model Free Approach
Gait Based Human Recognition with Various Classifiers Using Exhaustive Angle Calculations in Model Free Approach作者机构：Department of ECE Syed Ammal Engineering College Ramanathapuram India Department of ECE Government College of Engineering Salem India Department of ECE Thiagarajar College of Engineering Madurai India
出 版 物：《Circuits and Systems》 (电路与系统（英文）)
年 卷 期：2016年第7卷第8期
页 面：1465-1475页
学科分类：08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置]
主 题：Gait Recognition CASIA Gait Dataset B Classifiers
摘 要：Human Gait recognition is emerging as a supportive biometric technique in recent years that identifies the people through the way they walk. The gait recognition in model free approaches faces the challenges like speed variation, cloth variation, illumination changes and view angle variations which result in the reduced recognition rate. The proposed algorithm selected the exhaustive angles from head to toe of a person, and also height and width of the same subject. The experiments were conducted using silhouettes with view angle variation, and cloth variation. The recognition rate is improved to the extent of 91% using Support vector machine classifier. The proposed method is evaluated using CASIA Gait Dataset B (The institute of Automation, ChineseAcademy of Sciences), China. Experimental results demonstrate that the proposed technique shows promising results using state of the art classifiers.
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