Infrared gait recognition based on wavelet transform and support vector machine

Xue, Zhaojun; Ming, Dong; Song, Wei; Wan, Baikun; Jin, Shijiu

doi:10.1016/j.patcog.2010.03.011

Cited by 143 publications

(76 citation statements)

References 4 publications

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“…The methods in [26,27,28,11] aim to achieve invariance to carrying conditions. The method based on spatiotemporal motion characteristics, statistical and physical parameters (STM-SPP) [26] analyses the shape of a silhouette contour using Procrustes shape analysis at the double support phase and elliptic Fourier descriptors (EFDs) at ten phases of a gait period.…”

Section: Related Workmentioning

confidence: 99%

“…An iterative local curve embedding algorithm is used in [28] to extract double helical signatures from the subject's limb to take into account of shape distortion due to a specific carrying condition, e.g., a briefcase in upright position. The method in [11] uses models to obtain 4 skeleton parameters by wavelet decomposition of a GEI and extract invariant moments for combining anatomical and behavioural gait characteristics. The use of thermal imaging enables it to achieve invariance to carrying conditions and lighting variation.…”

Section: Related Workmentioning

confidence: 99%

“…Model-based methods (e.g., [8,9,10,11]) characterise a human subject using a structural model to measure time-varying gait parameters, e.g., gait period, stance width and stride length, and a motion model to analyse the kinematic and dynamical motion parameters of the subject, e.g., rotation patterns of hip and thigh, joint angle trajectories and orientation change of limbs.…”

Section: Introductionmentioning

confidence: 99%

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Robust view-invariant multiscale gait recognition

Das

Tjahjadi

2015

Pattern Recognition

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The paper proposes a two-phase view-invariant multiscale gait recognition method (VI-MGR) which is robust to variation in clothing and presence of a carried item. In phase 1, VI-MGR uses the entropy of the limb region of a gait energy image (GEI) to determine the matching gallery view of the probe using 2-dimensional principal component analysis and Euclidean distance classifier. In phase 2, the probe subject is compared with the matching view of the gallery subjects using multiscale shape analysis. In this phase, VI-MGR applies Gaussian filter to a GEI to generate a multiscale gait image for gradually highlighting the subject's inner shape characteristics to achieve insensitiveness to boundary shape alterations due to carrying conditions and clothing variation. A weighted random subspace learning based classification is used to exploit the high dimensionality of the feature space for improved identification by avoiding overlearning. Experimental analyses on public datasets demonstrate the efficacy of VI-MGR.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust view-invariant multiscale gait recognition

Das

Tjahjadi

2015

Pattern Recognition

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“…It is formulated as the sum each entropy, allowing the pseudo -additive property, defined in equation (3). We try to maximize the information measure between the two classes (object and background).…”

Section: Image Thresholding Based On Shannon and Tsallis Entropiesmentioning

confidence: 99%

“…Since, the edge is a prominent feature of an image; it is the front-end processing stage in object recognition and image understanding system. The detection results benefit applications such as optical character recognition [2], infrared gait recognition [3,4], automatic target recognition [5], detection of video changes [6], and medical image applications [7].…”

Section: Introductionmentioning

confidence: 99%

Novel Approach of Edges Detection for Digital Images Based On Hybrid Types of Entropy

El-Sayed¹,

Bahgat²,

Abdel‐Khalek³

2013

Appl. Math. Inf. Sci.

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Edges detection of digital images is used in a various fields of applications ranging from real-time video surveillance and traffic management to medical imaging applications. Most of the classical methods for edge detection are based on the first and second order derivatives of gray levels of the pixels of the original image. These processes give rise to the exponential increment of computational time. This paper shows the new algorithm based on both the Tsallis entropy and the Shannon entropy together for edge detection using split and merge technique. The objective is to find the best edge representation and minimize the computation time. A set of experiments in the domain of edge detection are presented. An edge detection performance compared to the previous classic methods, such as Canny, LOG, and Sobel. Analysis show that the effect of the proposed method is better than those methods in execution time and also is considered as easy implementation

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Human gait and Clinical Movement Analysis

Abu‐Faraj

Harris

Smith

et al. 2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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Human locomotion is an acquired yet complex behavior requiring little thought during routine activities. It involves the integration of intricate sensory information within the nervous system, resulting in motor commands to control muscle contraction, and subsequent joint movement. Nevertheless, the understanding of the development of coordinated gait activity is lacking, despite numerous and profound advances in science and technology. As such, the quest for knowledge in the field of Human Motion Analysis pertaining to normal and pathological gait poses a challenge to various disciplines, such as biomechanical engineering, orthopedics, physical medicine and rehabilitation, kinesiology, physical therapy, and sports medicine. This manuscript address Human Motion Analysis with a perspective on its evolutionary development, its present status, and a forecast of its future. A representation of the physiological basis of locomotion and some relevant anatomical terminology and gait‐related characteristics and terminology is also included. The article contains a substantial coverage of gait analysis methodologies and systems, with emphasis on systems' accuracy and reliability. A delineation of biomechanical modeling of gait data, including ground reaction forces, plantar pressures, kinematics, kinetics, dynamic electromyography, and energy expenditure is also presented. Additionally, a section on foot and ankle motion analysis is provided. The manuscript concludes by addressing clinical interpretation and decision making.

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Infrared gait recognition based on wavelet transform and support vector machine

Cited by 143 publications

References 4 publications

Robust view-invariant multiscale gait recognition

Robust view-invariant multiscale gait recognition

Novel Approach of Edges Detection for Digital Images Based On Hybrid Types of Entropy

Human gait and Clinical Movement Analysis

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