Our individual walking styles, much like snowflakes, are unique. With this in mind, computer scientists have developed a powerful new footstep-recognition system using AI, and it could theoretically replace retinal scanners and fingerprinting at security checkpoints, including airports.
Neural networks can find telltale patterns in a person’s gait that can be used to recognize and identify them with almost perfect accuracy, according to new research published in IEEE Transactions on Pattern Analysis and Machine Intelligence. The new system, called SfootBD, is nearly 380 times more accurate than previous methods, and it doesn’t require a person to go barefoot in order to work. It’s less invasive than other behavioral biometric verification systems, such as retinal scanners or fingerprinting, but its passive nature could make it a bigger privacy concern, since it could be used covertly.
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