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This paper proposes a method of gait recognition using a convolutional neural network (CNN). Inspired by the great successes of CNNs in image recognition tasks, we feed in the most prevalent image-based gait representation, that is, the gait energy image (GEI), as an input to a CNN designed for gait recognition called GEINet. More specifically, GEINet is composed of two sequential triplets of convolution,...
This paper describes a method of discriminant analysis for cross-view recognition with a relatively small number of training samples. Since appearance of a recognition target (e.g., face, gait, gesture, and action) is in general drastically changes as an observation view changes, we introduce multiple view-specific projection matrices and consider to project a recognition target from a certain view...
We constructed a large-scale multi-quality multi-modal biometric score database to advance studies on quality-dependent score-level fusion. In particular, we focused on single sensor-based multi-modal biometrics because of their advantages of simple system construction, low cost, and wide availability in real situations such as CCTV footage-based criminal investigation, unlike conventional individual...
Gait recognition has potential to recognize subject in CCTV footages thanks to robustness against image resolution. In the CCTV footage, several body-regions of subjects are, however, often un-observable because of occlusions and/or cutting off caused by limited field of view, and therefore, recognition must be done from a pair of partially observed data. The most popular approach to recognition from...
This paper describes a method for score-level fusion in multi-cue two-class classification problems. Fusion based on the probability density function (PDF) of multiple scores given for each class is a promising approach because it guarantees optimality as long as the estimated PDFs are correct. Instead of lattice-type control points used in previous non-parametric density-based approaches, floating...
Gait is a unique and promising behavioral biometrics which allows to authenticate a person even at a distance from the camera. Since a matching pair of gait features are often drawn from different views due to differences in camera position/attitude and walking directions in the real world, it is important to cope with cross-view gait recognition. In this paper, we propose a discriminative approach...
Gait recognition is a method of biometric person authentication from his/her unconscious walking manner. Unlike the other biometrics such as DNA, fingerprint, vein, and iris, the gait can be recognized even at a distance from a camera without subjects' cooperation, and hence it is expected to be applied to many fields: criminal investigation, forensic science, and surveillance. However, the absence...
This paper describes a method of gait recognition using multiple gait features in conjunction with score-level fusion techniques. More specifically, we focus on the state-of-the-art period-based gait features such as a gait energy image, a frequency-domain feature, a gait entropy image, a chronogait image, and a gait flow image. In addition, we employ various types of the score-level fusion approaches...
This paper proposes a method of gait recognition using not only shape feature but also motion feature from silhouette image sequences. The inner silhouette motion called pseudo motion is constructed by dividing the silhouette shape into small clusters and by computing many-to-many correspondence via earth mover's morphing framework. The raw pseudo motion, however, tends to be locally fluctuated in...
Gait recognition performance is often degraded by intra-subject gait fluctuations such as temporal fluctuations due to non-uniform evolution of phase (gait stance) and spatial fluctuations in arm swings or posture within the same phase. Therefore, we first propose a method for gait recognition using a phase-normalized image sequence to overcome the temporal fluctuations. However, it has been noticed...
Pattern recognition problems often suffer from the larger intra-class variation due to situation variations such as pose, walking speed, and clothing variations in gait recognition. This paper describes a method of discriminant subspace analysis focused on situation cluster pair. In training phase, both a situation cluster discriminant subspace and class discriminant subspaces for the situation cluster...
In the biometric verification, authentication is given when a distance of biometric signatures between enrollment and test phases is less than an acceptance threshold, and the performance is usually evaluated by a so-called Receiver Operating Characteristics (ROC) curve expressing a trade off between False Rejection Rate (FRR) and False Acceptance Rate (FAR). On the other hand, it is also well known...
We propose a method of gait silhouette transformation from one speed to another to cope with walking speed changes in gait identification. When a person changes his/her walking speed, dynamic features (e.g. stride and joint angle) are changed while static features (e.g. thigh and shin lengths) are unchanged. Based on the fact, firstly, static and dynamic features are separated from gait silhouettes...
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