Is Gait Recognition the Next Big Thing in Biometric Identity Verification?

Imagine walking towards a building where high-def cameras recognize your gait pattern and match it with your face as an added screening layer. Even if your face is occluded, gait analysis will recognize you as who you are. It will save time for standing in line or passing through security gates.

In this blog, we will understand Human Gait Analysis and look into the facts and theory pertinent to the technicalities, benefits, and challenges involved in implementing gait biometrics for human identity verification.

What is Gait Recognition?

Gait recognition is a method of biometric identity verification that recognizes individuals by their pattern of walking including walking style and pace. Advanced forensics and machine learning (ML) algorithms have enabled Gait Recognition to identify persons from a distance.

Why is Gait Recognition needed?

The answer is that whenever a biometric trait used for identity proofing fails due to a limitation, another one is needed. For example, in the case of fingerprint scanning and facial recognition, it’s used mostly consensual and can’t be used for identifying individuals approaching certain premises from a distance. Gait recognition technology addresses this concern as it can detect a person from a particular distance. 

Different Types of Gait Recognition System

Model-Based Gait Recognition

1. 3D Modeling: It uses body models to analyze joint movements recorded by high-def cameras (sometimes thermal imaging is used in it).
2. Kinematic Features: It focuses on the dynamics of walking patterns of users presented to the camera.

Appearance-Based Approach

1. Silhouette Analysis: It uses the outline of the person’s body in motion presented to the system.
2. Gait Energy Image (GEI): It captures average motion over time to form a unique signature.

Sensor-Based Gait Recognition

1. Wearable Devices: It use sensors like accelerometers and gyroscopes to track body movement from a distance.
2. Smartphone: It utilizes built-in sensors to gather gait data which is highly accurate.

How Does Gait Recognition System Work?

According to research, most gait recognition systems depend on the canonical view (side view) of a person presented to the camera. It also depends on the factor of a person’s distance from the camera and whether is it increasing or decreasing or linear i.e. a person is moving towards the camera or moving away from the camera. For a better understanding view the following graphical element:

Multiple researchers have attempted to fortify the accurate use of gait recognition for user identification. For example, nearly 20,000-foot movements from 127 people were recorded under a controlled environment using foot sensors and cameras. This data was presented to neural networks for training them and achieving nearly 100% accuracy,  the ML systems used spatial and temporal characteristics of people’s footprints to identify users.

Technologies Used in Gait Biometrics

As far as technologies involved in gait recognition, here are a few major ones:

• Video Surveillance: Cameras capture movement, often using standard or infrared video.
• Computer Vision: Analyzes video footage to detect and track individuals.
• Machine Learning: Algorithms model gait patterns and improve recognition accuracy.
• Image Processing: Enhances video quality and extracts relevant features.
• Biometrics: Compares gait data against existing profiles for identification.
• Deep Learning: Advanced neural networks refine pattern recognition and adaptability.

Where Gait Recognition is a Better Fit?

Gait Recognition systems are found beneficial in recognizing individuals when:

• There’s a threat of a potentially dangerous individual approaching a building with harmful intentions for example a terrorist trying to break into a government building or robbers approaching a bank.
• To identify runaway prisoners.
• To identify customers of banks and make informed decisions before they enter the premises.
• Monitoring of heavily crowded public spaces like sports stadiums.
• It can be used as a personalized home automation system to recognize residents of a vicinity.

Human Gait Analysis vs. Facial Recognition

There’s no such need to compare distinct biometric technologies if they are complimenting each other. There are domains in which the use of facial recognition supersedes human gait recognition and vice versa. However, here is a brief comparative analysis of gait recognition vs. face recognition to understand both as separate biometric identity entities.

Major Considerations in Human Gait Scan

Human gait scan requires a high level of precision and accuracy to ensure the minimum possible errors in identifying people. Though impersonating someone’s gait is quite difficult but not impossible. It is possible that someone of the same height and stature can wear the same dress, mimic someone’s gait through a lot of practice, and then attempt a spoofing gait scan. Additionally, there is no actual mechanism where gait recognition alone can stop this spoof attack if the imposter is highly trained. 

Even though after achieving 95% to 99% accuracy in different aspects of gait recognition the margin of error and imposter attack possibilities remain a challenge.

This is why it is always recommended to use gait recognition alongside other biometrics to strengthen identity verification.

Closing the Loophole with Facial Recognition

The best choice is to use both face recognition and gait recognition through the same recording devices. It is because both facial recognition and gait recognition can easily be implemented via the same cameras and recording devices so the cost of installing extra hardware will be reduced. Also, facial recognition and gait recognition closely supplement each other having the same goal which is recognizing a person through an image or a video. Furthermore, facial recognition is the most unconstrained biometric identity verification mechanism that can boost the results of identity proofing with gait recognition.

Liveness Detection: The Lifeline of Biometrics

Liveness Detection is the key to strengthened biometrics. From Iris scanning to facial recognition, it is considered the most vital factor that builds the foundation of a robust biometric security system. When the gait recognition system is implemented, it is obvious that it will only work on alive human beings so again there will be a systematic limitation the impersonator can’t be verified as the human gait presented is coming from a live person yet it can either be an imposter or a genuine user. Therefore, it is highly important to use facial liveness detection where a person is present at a certain distance.

Recent Developments in Gait Recognition Systems

Machine Learning has become advanced and so are Gait Recognition systems by introducing AI models. Artificial Intelligence is said to have helped almost every digital sector in terms of process automation to achieve greater speed and accuracy in results. Gait Recognition systems governed by AI are far more accurate and fast than manually monitored systems. Further developments are aimed at achieving 100% accuracy by removing all margins of errors from it.

Final Word

Gait Recognition technology is a biometric technique that seems to be fading away as facial recognition is becoming more sophisticated every day. Despite this fact, the benefits of gait recognition can’t be ignored as this technology offers a unique way of identifying users and potentially harmful people from a distance. The best way to enhance biometric gait recognition is to use multi-factor biometric identity verification, especially using a combo of facial recognition and gait recognition.