DST examines gait recognition for personal identification

Australian defence scientists are exploring how individual walking styles may help in personal identification.

For decades, automated facial recognition systems have been used by law enforcement agencies to identify persons of interest. However, these systems can have limitations.  Low lighting, poor picture resolution, facial coverings, even different facial expressions can impede performance.

Scientists are now 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, DST Group scientists Sau Yee Yiu and Gary Hanly are part of a team analysing different methods for capturing gait data.

Ms Yiu explains that gait recognition has certain advantages over facial recognition.

“Gait has the benefit of being plainly visible, perceivable at a distance, and is something that can be captured non-invasively,” she says. “The purpose of our research is to demonstrate that different gait features can be extracted from a person and used to accurately identify them.”

The use of gait recognition for identification is not entirely new.  It has been used in hospital settings to monitor the elderly and in sports science.

However, the researchers have acknowledged potential 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 that will enable gait features to be extracted from multiple people in a scene.