Biometric technology has contributed significantly to propelling civilization forward, making possible a degree of accuracy rate in identification and authentication needed for society to rest its confidence in the inner workings of law enforcement, banking, healthcare, digital transactions, elections, among other endeavors.
The most common modalities of biometric identification and authentication had so far centered around fingerprint, iris and face. Yet the impetus to take things just a little further has prompted researchers to investigate other modalities which are less obtrusive.
Human gait recognition is one such unobtrusive biometric modality that is gaining attention. Unlike biometrics using fingerprint, face, vein pattern, or iris scan which measure physical biometric traits, gait recognition is a behavioral biometric modality that identifies people based on their gait dynamics and motion features.
Gait recognition technology is hinged on the idea that individuals have a unique and nuanced way of walking which can be recorded, measured, and analyzed by gait recognition software for human identification and authentication purposes. While general walking movements appear the same to the naked eye, there are minute variances in timing and magnitude from one person to another.
Such gait sequence and variations are unique, making human gait patterns strong biometric identifiers to differentiate individuals' gait characteristics and motion features. Gait analysis considers gait shape and gait dynamics such as step length, step width, speed and cycle time along with kinematic factors such as rotations of the joints in the hip, knee and ankle, mean joint angles of the hip, knee and ankle and thigh, trunk and foot angles.
Other factors accounted for are the relationship between step length and the height of an individual.
In contrast to well-known biometric devices such as fingerprint scanners and facial recognition terminals, the three main types of gait recognition techniques are those based on the automatic analysis of video imagery from video cameras or wearable sensors, the second method uses radar, and the third uses sensors embedded in smart phones and other gadgets.
Already, studies are being made to test the suitability of gait recognition in actual use cases such as hardening smartphones against identity theft using accelerometers and gyroscopes.
One big benefit of this is that the user does not need to perform any extra action as the needed data is continuously generated while the person walks normally. This unobtrusiveness of gait-based authentication makes it a viable and powerful way to identify and authenticate individuals, especially when paired with other biometric modalities for a persistent and continuous multimodal protection for smartphones mobile devices.
Indeed, this method has already shown an ability to rapidly identify users with a high degree of confidence and preventing sensitive data from being leaked.
Another interesting use case is where pressure-based gait-authentication systems are installed on the floor to capture natural footsteps which are then used to distinguish individual gait patterns. This biometric modality allows for physical access control that is completely natural and unobtrusive.
Unlike most biometric traits which require formal user registration and require users to actively present themselves for inspection, gait samples for registration can be acquired silently and unobtrusively making the whole process painless for both staff and those seeking to get in the facilities. With everything being done inconspicuously, the method would be unknown to would-be imposters, thereby deterring attacks.
Biometric identity and authentication have come a long way in engendering countless innovations and conveniences into modern life and are still ceaselessly evolving. With new modalities such as gait recognition rapidly developing and are set to be ready for prime time not too long from now, identity and authentication continue to be at the forefront of technologies that work to improve societies.
Gait recognition biometrics is the use of an individual's unique gait characteristics (walking pattern) to identify them. This type of biometrics can be used for both identification and verification purposes. Several methods exist for identifying a person's gait features, the most popular of which involves monitoring aspects like the individual's body type, stride, and pace.
Gait biometrics is used in a variety of settings, including security and surveillance, law enforcement, and healthcare. In security and surveillance applications, it can be used to track and monitor people as they move around a given area. Additionally, gait biometrics can be used in physical access control to authenticate individuals as they enter or exit a secured area.