Walk this way: A better way to identify gait differences

November 08, 2017

Osaka - Biometric-based person recognition methods have been extensively explored for various applications, such as access control, surveillance, and forensics. Biometric verification involves any means by which a person can be uniquely identified through biological traits such as facial features, fingerprints, hand geometry, and gait, which is a person's manner of walking.

Gait is a practical trait for video-based surveillance and forensics because it can be captured at a distance on video. In fact, gait recognition has been already used in practical cases in criminal investigations. However, gait recognition is susceptible to intra-subject variations, such as view angle, clothing, walking speed, shoes, and carrying status. Such hindering factors have prompted many researchers to explore new approaches with regard to these variations.

Research harnessing the capabilities of deep learning frameworks to improve gait recognition methods has been geared to convolutional neural network (CNN) frameworks, which take into account computer vision, pattern recognition, and biometrics. A convolutional signal means combining any two of these signals to form a third that provides more information.

An advantage of a CNN-based approach is that network architectures can easily be designed for better performance by changing inputs, outputs, and loss functions. Nevertheless, a team of Osaka University-centered researchers noticed that existing CNN-based cross-view gait recognition fails to address two important aspects.

"Current CNN-based approaches are missing the aspects on verification versus identification, and the trade-off between spatial displacement, that is, when the subject moves from one location to another," study lead author Noriko Takemura explains.

Considering these two aspects, the researchers designed input/output architectures for CNN-based cross-view gait recognition. They employed a Siamese network for verification, where an input is a pair of gait features for matching, and an output is genuine (the same subjects) or imposter (different subjects) probability.

Notably, the Siamese network architectures are insensitive to spatial displacement, as the difference between a matching pair is calculated at the last layer after passing through the convolution and max pooling layers, which reduces the gait image dimensionality and allows for assumptions to be made about hidden features. They can therefore be expected to have higher performance under considerable view differences. The researchers also used CNN architectures where the difference between a matching pair is calculated at the input level to make them more sensitive to spatial displacement.

"We conducted experiments for cross-view gait recognition and confirmed that the proposed architectures outperformed the state-of-the-art benchmarks in accordance with their suitable situations of verification/identification tasks and view differences," coauthor Yasushi Makihara says.

As spatial displacement is caused not only by view difference but also walking speed difference, carrying status difference, clothing difference, and other factors, the researchers plan to further evaluate their proposed method for gait recognition with spatial displacement caused by other covariates.
-end-


Osaka University

Related Gait Articles from Brightsurf:

Restoring mobility by identifying the neurons that make it possible
Partial mobility can be restored in rodents with impaired spinal cords.

A data treasure for gait analysis
The St. Pölten UAS and the Austrian general accident insurance institution AUVA have made one of the biggest data records for automated gait analysis worldwide openly accessible.

Cognition and gait speed often decline together, study shows
Measures of cognition and gait speed largely paralleled each other in a San Antonio study of 370 participants that included 9½ years of follow-up.

AI-powered shoes unlock the secrets of your sole
Researchers at Stevens Institute of Technology have developed an AI-powered, smart insole that instantly turns any shoe into a portable gait-analysis laboratory.

Monty Python's silly walk: A gait analysis and wake-up call to peer review inefficiencies
Fifty years ago, Monty Python's famous sketch, 'The Ministry of Silly Walks,' first aired.

Hypertension in young adulthood associated with cognitive decline in middle age
Research from Tel Aviv University indicates that high blood pressure in young adulthood is associated with cognitive decline and gait impairment in middle age.

How decline in memory, gait speed are associated with dementia risk
The risk of dementia in adults 60 and older who experience declines in both memory and gait speed was compared with adults who experience no decline or decline in either memory or gait speed only in this observational meta-analysis that included six studies with about 8,700 participants from the US and Europe.

Looking at the way we walk can help predict cognitive decline
The way people walk is an indicator of how much their brains, as well as their bodies, are aging.

Your video can ID you through walls with help of WiFi
Researchers in the lab of UC Santa Barbara professor Yasamin Mostofi have enabled, for the first time, determining whether the person behind a wall is the same individual who appears in given video footage, using only a pair of WiFi transceivers outside.

Stroke patients relearning how to walk with peculiar shoe
Clinical trials have been completed on a therapeutic shoe engineered to improve stroke recovery.

Read More: Gait News and Gait Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.