Footstep recognition as people identification: A Systematic literature review

TL;DR

This systematic review analyzes various technologies and features used in footstep recognition for person identification, highlighting trends, common methods, and suggesting future research directions involving sensor fusion and data processing enhancements.

Contribution

It provides a comprehensive comparison of existing footstep recognition methods and features, and proposes combining sensors and data processing for improved accuracy.

Findings

Number of publications increased over time, especially in conferences.

Footstep features include power spectral density of sounds and vibrations.

Multiple technologies and features are used across studies.

Abstract

Footstep recognition is a relatively new biometric which aims to discriminate people using walking characteristics. There are several feature and technology have been adopted in various research. This study will attempt to show a comparative technology and feature which is offered each previous related works. We performed a broad manually search to find SLRs published in the time period 1st January 2006 to 30th November 2018. Our broad search found 12 SLRs articles refer to 3 similar technology and 5 cluster feature. In over time, the number of published footstep recognition has increased, especially in conference publications. The differences in footsteps can be known from the power spectral density of sounds and vibrations generated by footsteps. Every footstep of the human has a certain density of frequency, either from density of sounds or vibrations generated. To improve accurately of the result, this paper suggests furthermore research to combining several measuring sensor and data processing method