Biometric recognition by gait: A survey of modalities and features

• Published in: Computer vision and image understanding Vol. 167; pp. 1 - 27
• Main Authors: Connor, Patrick, Ross, Arun
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2018
• Subjects: Covariates; Features; Gait biometrics; Gait recognition; Ground reaction force; Silhouette; Features; Silhouette; Gait biometrics; Ground reaction force; Covariates; Gait recognition
• ISSN: 1077-3142; 1090-235X
• DOI: 10.1016/j.cviu.2018.01.007

•A comprehensive survey of biometric gait recognition based on vision, underfoot pressure, accelerometry, and audio sensory modalities.•A review of the factors that impact gait recognition performance (e.g., walking speed, clothing, footwear, etc.) and the influence of time lapse.•A discussion on the future of gait biometrics and the challenges and open problems that are yet to be addressed in the field. The scientific literature on automated gait analysis for human recognition has grown dramatically over the past 15 years. A number of sensing modalities including those based on vision, sound, pressure, and accelerometry have been used to capture gait information. For each of these modalities, a number of methods have been developed to extract and compare human gait information, resulting in different sets of features. This paper provides an extensive overview of the various types of features that have been utilized for each sensing modality and their relationship to the appearance and biomechanics of gait. The features considered in this work include (a) static and dynamic (temporal) features; (b) model-based and model-free visual features; (c) ground reaction force-based and finely resolved underfoot pressure features; (d) wearable sensor features; and (e) acoustic features. We also review the factors that impact gait recognition, and discuss recent work on gait spoofing and obfuscation. Finally, we enumerate the challenges and open problems in the field of gait recognition.