Gait Recognition With Shifted Energy Image and Structural Feature Extraction

Abstract

In this paper, we present a novel and efficient gait recognition system. The proposed system uses two novel gait representations, the Shifted Energy Image and the Gait Structural Profile, that have increased robustness to some classes of structural variations. Furthermore, we introduce a novel method for the simulation of walking conditions and the generation of artificial subjects that are used for the application of Linear Discriminant Analysis. In the decision stage, the two representations are fused.Thorough experimental evaluation, conducted using one traditional and two new databases, demonstrates the advantages of the proposed system in comparison to current state-of-the-art systems.

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

“…Thereafter, the mean and variance of the distribution is obtained. Lee et al (2014b) TAMHI + HOG Euclidean distance Liu and Sarkar (2004) Averaged silhouette Euclidean distance Xu et al (2006) Averaged silhouette + CSA + DATER kNN Han and Bhanu (2006) GEI Euclidean distance Yang et al (2008) EGEI Euclidean distance Huang et al (2013) Modified GEI + Gabor Wavelets SVM Zhang et al (2009) DGEI + PCA + Locality preserving projections Euclidean distance Xu and Zhang (2010) GEI + Fuzzy PCA kNN + Euclidean distance Moustakas et al (2010) GEI + Radial integration transform Probability Xu et al (2012) GEI + Gabor-PDF Locality constrained group sparse representation Zhang et al (2010a) AEI + 2D locality preserving projections kNN + Euclidean distance Huang and Boulgouris (2012) SEI + Linear discriminant analysis -Chen et al Murase and Sakai (1996) Parametric eigenspace trajectories Spatiotemporal correlation Huang et al (1999) PMS + Canonical analysis Spatiotemporal correlation Wang et al (2003a;2003b) PMS Procrustes distance Zhang et al (2010b) PMS + Shape context kNN + Shape context distance Zheng et al (2011) VTM L1-norm distance Kusakunniran et al (2011a) PSC kNN + Procrustes distance Kusakunniran et al (2011b) HSC kNN + Procrustes distance Mowbray and Nixon (2003) Fourier descriptors kNN + Euclidean distance Tian et al (2004) Fourier descriptors DTW Lu et al (2008) Fourier descriptors (key frame profile) kNN Yuan et al (2015) Fourier descriptors (key frame) Canonical Time Warping Ohara et al (2004) 3D Fourier descriptors Cross correlation Choudhury and Tjahjadi (2012) PMS + elliptical Fourier descriptors Procrustes distance + dissimilarity score Lee et al (2013) Circular shifting + Interpolation + Fourier descriptor Product of Fourier coefficients Boulgouris and Chi (2007) Radon transform + LDA Euclidean distance Table 5. Summary of model-free approaches (distribution-based representation) Literature Gait features Classifier/distance metric …”

Multilinear Laplacian discriminant analysis for gait recognition

“…Gait flow image (GFI) by Toby et al [8] computes optical flow field and uses threshold to activate pixel for binary image and then averaging is used for GFI. The shifted energy image by Huang and Boulgouris [9] has processed misalignment of head and body position over complete cycle for improvement of recognition rate.…”

“…Gait flow image (GFI) by Toby et al [8] computes optical flow field and uses threshold to activate pixel for binary image and then averaging is used for GFI. The shifted energy image by Huang and Boulgouris [9] has processed misalignment of head and body position over complete cycle for improvement of recognition rate. The shape variation-based Frieze Pattern by Liu et al [10], gait entropy image by Bashir et al [12] and frequency-domain features by Makihara et al [14] are effective gait descriptors that has appealed more research towards statistical methods for feature extraction.…”

“…These set of advantages offer gait as unique candidate for video surveillance application [6]. Number of efforts have been made by researchers to improve recognition rate under experimental environment [7][8][9][10], however, the performance in presence of diverse factor called as covariates; degrades. Thus, robust human gait recognition offers unique challenge for extraction of discriminative features in presence of covariates.…”

An Extraction Method Based on Invariance Geometric Feature

“…Image recognition is a technique to process, analyze and understand different type of the object in an image by using computer, which is used very widely [1][2][3]. It can be completely finished after preprocessing, segmentation, feature extraction and classification.…”