Human gait recognition: A systematic review

Rani, Veenu; Kumar, Munish

doi:10.1007/s11042-023-15079-5

Cited by 17 publications

(7 citation statements)

References 120 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another taxonomy based on environmental issues, environmental lighting sources, imaging cameras, and individual appearance is presented in [ 75 ]. In [ 8 ], the authors proposed a taxonomy that highlights the different classifiers, such as deep learning-based and traditional-based. Finally, in [ 9 ], there is a proposed taxonomy that is separated into four parts.…”

Section: Taxonomymentioning

confidence: 99%

“…Both kinds of biometrics have unique benefits and can be used in conjunction with one another to strengthen security and authentication protocols. Physical biometric methods include approaches such as retina scanning, face recognition [ 2 ], fingerprint [ 3 ] and iris scanning [ 4 ], while behavioral biometric methods include voice recognition [ 5 ], keystroke recognition [ 6 ], gait recognition [ 7 , 8 , 9 , 10 ], and signature recognition [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Video sequences of gait information can be taken from a distance with low spatial resolution. So, gait recognition can identify individuals from a distance based on their walking style, which makes it ideal for applications where it is not possible to be close to the individual being identified [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…In the last decades, the majority of studies in the literature have been published based on vision-based gait recognition that is camera based as opposed to sensor-based or pose-based gait recognition [ 30 ]. The previous studies mainly focused on traditional machine learning approaches [ 8 ]. However, at the current time, the published works clearly focus on deep learning approaches.…”

Section: Introductionmentioning

confidence: 99%

“…The review papers that have been written about gait recognition using non-vision-based methods focus on the literature up until 2018. Some of the vision-based review papers [ 7 , 8 , 9 ] look at the literature that has been published up until 2020. Regardless of this, deep learning has recently made a number of significant advancements in the field of gait recognition.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Person Recognition Based on Deep Gait: A Survey

Khaliluzzaman

Uddin

Deb

et al. 2023

Sensors

View full text Add to dashboard Cite

Gait recognition, also known as walking pattern recognition, has expressed deep interest in the computer vision and biometrics community due to its potential to identify individuals from a distance. It has attracted increasing attention due to its potential applications and non-invasive nature. Since 2014, deep learning approaches have shown promising results in gait recognition by automatically extracting features. However, recognizing gait accurately is challenging due to the covariate factors, complexity and variability of environments, and human body representations. This paper provides a comprehensive overview of the advancements made in this field along with the challenges and limitations associated with deep learning methods. For that, it initially examines the various gait datasets used in the literature review and analyzes the performance of state-of-the-art techniques. After that, a taxonomy of deep learning methods is presented to characterize and organize the research landscape in this field. Furthermore, the taxonomy highlights the basic limitations of deep learning methods in the context of gait recognition. The paper is concluded by focusing on the present challenges and suggesting several research directions to improve the performance of gait recognition in the future.

show abstract

Section: Taxonomymentioning

confidence: 99%