Footstep recognition as people identification: A Systematic literature review
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Accesso online: | |
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| _version_ | 1866916495145041920 |
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| author | Rachmat, Arif |
| author_facet | Rachmat, Arif |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_16688 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Footstep recognition as people identification: A Systematic literature review Rachmat, Arif Human-Computer Interaction 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 |
| title | Footstep recognition as people identification: A Systematic literature review |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2411.16688 |