Your Gait Can Now Help in Your Identification

Your Gait Can Now Help in Your Identification

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For decades, automated facial recognition systems have been used by law enforcement agencies to identify persons of interest. However, these systems are not without their limitations. Low lighting, poor picture resolution, facial coverings, and facial expressions can impede performance. 

Gait recognition has the potential to replace facial recognition in certain conditions, as it is

plainly visible, perceivable at a distance and is something that can be captured non-invasively. 

Defense scientists in Australia are exploring how individual walking styles may help in personal identification. The team is exploring how the characteristics of an individual’s gait could help in establishing a person’s identity. 

Working with researchers from the University of Adelaide and Swordfish Computing, Australian Defense scientists Sau Yee Yiu and Gary Hanly are part of a team analysing different methods for capturing gait data.

Typically the focus has been on obtaining optical flow data and skeletal tracking data using a video camera or motion-sensing technology, however the team has also examined a method which uses ground-based pressure pads to measure the various forces at play when walking. 

The purpose of the research is to demonstrate that different gait features can be extracted from a person and used to accurately identify them.

Gait recognition has been used in hospital settings to monitor the elderly and in sports science. However, there are limitations: An individual may change their gait when walking in a crowded space, for example. Even the health of the individual, their clothing and camera-viewing angles can change or obscure the walking pattern of a person and so affect recognition accuracy. There is also “gait spoofing” where an individual may intentionally alter their gait.

Future research is planned to address these limitations, including improvements to algorithms, which will enable gait features to be extracted from multiple people in a scene.

Using gait recognition in conjunction with face or other biometrics, or just by including other descriptors of a person such as their height, age and gender could improve the identification performance, as reported by