Journal ArticleDOI
Robust gait recognition: a comprehensive survey
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TLDR
A comprehensive overview of existing robust gait recognition methods is provided to provide researchers with state of the art approaches in order to help advance the research topic through an understanding of basic taxonomies, comparisons, and summaries of the state-of-the-art performances on several widely used gait Recognition datasets.Abstract:
Gait recognition has emerged as an attractive biometric technology for the identification of people by analysing the way they walk. However, one of the main challenges of the technology is to address the effects of inherent various intra-class variations caused by covariate factors such as clothing, carrying conditions, and view angle that adversely affect the recognition performance. The main aim of this survey is to provide a comprehensive overview of existing robust gait recognition methods. This is intended to provide researchers with state of the art approaches in order to help advance the research topic through an understanding of basic taxonomies, comparisons, and summaries of the state-of-the-art performances on several widely used gait recognition datasets.read more
Citations
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Journal ArticleDOI
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
TL;DR: A hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted by a convolutional neural network and a recurrent neural network to obtain good person identification and authentication performance.
Journal ArticleDOI
A comprehensive overview of feature representation for biometric recognition
TL;DR: A comprehensive overview of the different existing feature representation techniques is presented by introducing simple and clear taxonomies as well as effective explanation of the prominent techniques to guide the neophyte and provide researchers with state-of-the-art approaches.
Journal ArticleDOI
View-Invariant Gait Recognition With Attentive Recurrent Learning of Partial Representations
TL;DR: A network that first learns to extract gait convolutional energy maps (GCEM) from frame-level convolutionAL features then adopts a bidirectional recurrent neural network to learn from split bins of the GCEM, thus exploiting the relations between learned partial spatiotemporal representations.
Journal ArticleDOI
Gait recognition invariant to carried objects using alpha blending generative adversarial networks
TL;DR: This paper proposes a robust method for gait recognition against various COs by reconstructing a gait template without COs using a conventional generative adversarial network and feeds it into a state-of-the-art discrimination network for gact recognition.
Journal ArticleDOI
Gait Recognition Based on Deep Learning: A Survey
Claudio Filipi Gonçalves dos Santos,Diego de Souza Oliveira,Leandro A. Passos,Rafael Gonçalves Pires,Daniel Felipe Silva Santos,Lucas Pascotti Valem,Thierry P. Moreira,Marcos Cleison S. Santana,Mateus Roder,Jo Paulo Papa,Danilo Colombo +10 more
TL;DR: A surveyed compilation of recent works regarding biometric detection through gait recognition with a focus on deep learning approaches, emphasizing their benefits and exposing their weaknesses and categorized and characterized descriptions of the datasets, approaches, and architectures employed to tackle associated constraints.
References
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Proceedings ArticleDOI
Human identification system based on feature level fusion using face and gait biometrics
TL;DR: The achieved results showed that the integrated face and gait features carry the most discriminating power compared to any individual biometric.
Proceedings ArticleDOI
Haralick features for GEI-based human gait recognition
TL;DR: A supervised feature extraction method which is able to select discriminative features for human gait recognition under the variations of clothing and carrying conditions and hence to improve the recognition performances is proposed.
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Modelling, synthesis and characterisation of occlusion in videos
TL;DR: This study proposes an occlusion model based on the position and pose uncertainties of the moving subjects in a video that is able to characterise the level of Occlusion present in aVideo.
Journal ArticleDOI
Information set based gait authentication system
TL;DR: The proposed features outperform the existing features using IHC and are validated on three databases using Support Vector Machine, Euclidean Classifier and Improved Hanman Classifier.
Proceedings ArticleDOI
Multi-view discriminant analysis with tensor representation and its application to cross-view gait recognition
TL;DR: Experiments of cross-view gait recognition with two publicly available gait databases show the effectiveness of the proposed method in case where a training sample size is small.
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