Gait Recognition with Fuzzy Classification Using Shoulder Body Joint

Bharti, Jyoti; Gupta, Manju Lata

doi:10.7763/ijfcc.2013.v2.233

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…The final label is determined based on the highest proximity value. The application of fuzzy logic in gait recognition could be found in Roy and Sural (2009;Bharti and Gupta, 2013), among others.…”

Section: Pattern Recognition and Classificationmentioning

confidence: 99%

Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

Lee¹,

Tan²,

Lim³

2017

American Journal of Applied Sciences

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Gait has unique advantage at a distance when other biometrics cannot be used since they are at too low resolution or obscured, as commonly observed in visual surveillance systems. This paper provides a survey of the technical advancements in vision-based gait recognition. A wide range of publications are discussed in this survey embracing different perspectives of the research in this area, including gait feature extraction, classification schemes and standard gait databases. There are two major groups of the state-of-the-art techniques in characterizing gait: Model-based and motion-free. The model-based approach obtains a set of body or motion parameters via human body or motion modeling. The model-free approach, on the other hand, derives a description of the motion without assuming any model. Each major category is further organized into several subcategories based on the nature of gait representation. In addition, some widely used classification schemes and benchmark databases for evaluating performance are also discussed.

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Section: Pattern Recognition and Classificationmentioning

confidence: 99%

Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

Lee¹,

Tan²,

Lim³

2017

American Journal of Applied Sciences

View full text Add to dashboard Cite

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A type-2 fuzzy index to assess high heeled gait deviations using spatial-temporal parameters

Massoud

2021

Computer Methods in Biomechanics and Biomedical Engineering

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A Modified Walk Recognition System for Human Identification Based on Uncertainty Eigen Gait

Darwish¹,

El-Zoghabi²,

Hassen³

2014

IJMLC

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Abstract-Gait based recognition is one of the emerging new biometric technology for human identification, surveillance and other security applications. Gait is a potential behavioral feature to identify humans at a distance based on their motion. The use of new methods for handling inaccurate information about gait features is of fundamental important. This paper deals with the design of an intelligent gait recognition system using interval type-2 fuzzy K-nearest neighbor (IT2FKNN) for diminishing the effect of uncertainty formed by variations in energy deviation image (EDI). The proposed system is built on top of the well-known principal component analysis (PCA) method that is utilized to remove correlation between the features and also to reduce its dimensionality. Our system employs IT2FKNN to compute fuzzy within and in-between class scatter matrices of PCA to refine classification results. This employment makes the system able to distinguish between normal, abnormal and suspicious walk of a person so that an alarming action may be taken well in time. Interval type-2 fuzzy set is involved to extend the membership values of each gait signatures by using several initial K in order to handle and manage uncertainty that exist in choosing initial K. The result of the experiments conducted on gait database show that the proposed gait recognition approach can obtain encouraging accurate recognition rate.Index Terms-Biometric, gait recognition, interval type-2 fuzzy KNN, PCA.

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Gait Recognition with Fuzzy Classification Using Shoulder Body Joint

Cited by 3 publications

References 10 publications

Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

A type-2 fuzzy index to assess high heeled gait deviations using spatial-temporal parameters

A Modified Walk Recognition System for Human Identification Based on Uncertainty Eigen Gait

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