Gait recognition by fluctuations

Aqmar, Muhammad Rasyid; Fujihara, Yusuke; Makihara, Yasushi; Yagi, Yasushi

doi:10.1016/j.cviu.2014.05.004

Cited by 22 publications

(6 citation statements)

References 49 publications

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“…Aqmar et el. [34] described a gait recognition approach by suppressing and using gait fluctuations. Inconsistent synchronization between a pair of walking image sequences due to temporal fluctuations degrades the gait recognition performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Gait Recognition based on Measurements of Moving Human Legs Angles

Al-Ani

Mohammadi

AlyanNezhadi

2020

IJE

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Biometrics plays a crucial role in security systems. Gait recognition as an aspect of behavioral biometrics deals with identifying human based on the walking. In this research, we proposed a new method to identify people according to their gait characteristics. This approach is performed via several steps; a) the video frames of a walking subject is recorded. b) each video is decomposed into eight phases, wherein each phase, there are several frames. One frame per phase is selected. c) the extracted frame is segmented to separate the subject from the background. d) the image is converted to a binary image, and the skeletonization is applied to obtain the silhouette of the image. e) the fast Fourier transform is applied to each frame, and several statistical features are calculated. The average of the statistical measures for eight frames of a video is computed as a feature vector for the subject. Finally, the correlation is used to identify the subject based on the feature vector. The accuracy of 100% is achieved for the recognition of the subjects in the CASIA dataset.

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Section: Literature Reviewmentioning

confidence: 99%

Gait Recognition based on Measurements of Moving Human Legs Angles

Al-Ani

Mohammadi

AlyanNezhadi

2020

IJE

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“…The many studies then published their own version of an energy image adopted from the core principles of the GEI. One of such proposals includes the GFlucI -gait fluctuation image [52]. By applying a technique called Self-DTW, a variant of DTW, the silhouette sequences are phase-normalised.…”

Section: Notementioning

confidence: 99%

Trait of Gait: A Survey on Gait Biometrics

Isaac,

Elias,

Rajagopalan

et al. 2019

Preprint

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Gait analysis is the study of the systematic methods that assess and quantify animal locomotion. The research on gait analysis has considerably evolved through time. It was an ancient art, and it still finds its application today in modern science and medicine. This paper describes how one's gait can be used as a biometric. It shall diversely cover salient research done within the field and explain the nuances and advances in each type of gait analysis. The prominent methods of gait recognition from the early era to the state of the art are covered. This survey also reviews the various gait datasets. The overall aim of this study is to provide a concise roadmap for anyone who wishes to do research in the field of gait biometrics.

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“…Although this assumption is reasonable and widely used in the literature [7,18,41], we have also noted that the actually collected signal in some cases may vary in periods, i.e., cycle non-stationary. With the purpose of extending the method to these cases, we would employ a preprocessing, e.g., angle re-sampling [55] and phase estimation using dynamic time warping [56,57], in order to suppress such temporal non-stationary before applying it to monitoring non-stationary condition signals.…”

Section: Experimental Validationmentioning

confidence: 99%

Differential Equation-Based Prediction Model for Early Change Detection in Transient Running Status

Wen

Huang

et al. 2019

Sensors

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Early detection of changes in transient running status from sensor signals attracts increasing attention in modern industries. To achieve this end, this paper presents a new differential equation-based prediction model that can realize one-step-ahead prediction of machine status. Together with this model, an analysis of continuous monitoring of condition signal by means of a null hypothesis testing is presented to inspect/diagnose whether an abnormal status change occurs or not during successive machine operations. The detection operation is executed periodically and continuously, such that the machine running status can be monitored with an online and real-time manner. The effectiveness of the proposed method is demonstrated using three representative real-engineering applications: external loading status monitoring, bearing health status monitoring and speed condition monitoring. The method is also compared with those benchmark methods reported in the literature. From the results, the proposed method demonstrates significant improvements over others, which suggests its superiority and great potentials in real applications.

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Gait recognition by fluctuations

Cited by 22 publications

References 49 publications

Gait Recognition based on Measurements of Moving Human Legs Angles

Gait Recognition based on Measurements of Moving Human Legs Angles

Trait of Gait: A Survey on Gait Biometrics

Differential Equation-Based Prediction Model for Early Change Detection in Transient Running Status

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