has been cited by the following article(s):
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[1]
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Machine vision gait-based biometric cryptosystem using a fuzzy commitment scheme
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2019 |
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[2]
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Computer and Information Sciences
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2019 |
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[3]
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The comparative study of model-based and apprearance based gait recognition for leave bag behind
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2018 |
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[4]
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THE COMPARATIVE STUDY OF MODEL-BASED AND APPEARANCE BASED GAIT RECOGNITION FOR LEAVE BAG BEHIND
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2018 |
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[5]
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Enhanced Surveillance Using Integration of Gait Analysis with Iris Detection
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Advanced Computational and Communication Paradigms,
2018 |
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[6]
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Movement Disorder Detection via Adaptively Fused Gait Analysis based on Kinect Sensors
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2018 |
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[7]
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Review on Enhancement of Gait Recognition Using SURF and K-NN
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INTERNATIONAL JOURNAL FOR RESEARCH IN EMERGING SCIENCE AND TECHNOLOGY,
2017 |
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[8]
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Kinematic and vibration description of running pattern using empirical mode decomposition
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2017 |
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[9]
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MODEL-BASED 3D GAIT BIOMETRIC USING QUADRUPLE FUSION CLASSIFIER
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2017 |
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[10]
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Human locomotion analysis, classification and modeling of normal and pathological vertical ground reaction force signals in elderly
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Thèse,
2016 |
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[11]
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不受服饰携带物影响的步态识别方法
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计算机工程与应用,
2016 |
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[12]
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Human Gait Recognition Using Silhouettes.
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International Journal of Applied Engineering Research,
2015 |
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[13]
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Gait Recognition Based on Energy Accumulation Images
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Biometric Recognition,
2015 |
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[14]
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基于质心和轮廓关键点的步态识别
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Computer Engineering and Applications,
2015 |
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[15]
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Understanding human gait: A survey of traits for biometrics and biomedical applications
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2015 |
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[16]
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Reflection Removal and Feature Extraction Techniques in Non-cooperative Visible Eye Images for Iris Recognition
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Thesis,
2013 |
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[17]
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Human Identification Based Biometric Gait Features using MSRC
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International Journal of Advanced Research in Computer Engineering & Technology (IJARCET),
2013 |
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[18]
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Gait Pattern Retrieval from Motion Capture Data
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[1]
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Understanding human gait: A survey of traits for biometrics and biomedical applications
2015 International Conference on Energy Systems and Applications,
2015
DOI:10.1109/ICESA.2015.7503444
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[2]
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Biometric Recognition
Lecture Notes in Computer Science,
2015
DOI:10.1007/978-3-319-25417-3_54
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