Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method
Author:
, , , ,Year
: 2012
Abstract: This paper presents a human gait recognition algorithm based on a leg gesture separation. Main innovation in this paper is gait
recognition using leg gesture classification which is invariant to covariate conditions during walking sequence and just focuses on
underbody motions and a neuro-fuzzy combiner classifier (NFCC) which derives a high precision recognition system. At the end,
performance of the proposed algorithm has been validated by using the HumanID Gait Challenge data set (HGCD), the largest gait
benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition,
and time. And it has been compared to recent algorithm of gait recognition.
recognition using leg gesture classification which is invariant to covariate conditions during walking sequence and just focuses on
underbody motions and a neuro-fuzzy combiner classifier (NFCC) which derives a high precision recognition system. At the end,
performance of the proposed algorithm has been validated by using the HumanID Gait Challenge data set (HGCD), the largest gait
benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition,
and time. And it has been compared to recent algorithm of gait recognition.
Keyword(s): Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method
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Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method
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| contributor author | هادی صدوقی یزدی | en |
| contributor author | حسام جهانی فریمان | en |
| contributor author | Jaber Roohi | en |
| contributor author | Hadi Sadoghi Yazdi | fa |
| contributor author | Hessam Jahani Fariman | fa |
| date accessioned | 2020-06-06T14:37:10Z | |
| date available | 2020-06-06T14:37:10Z | |
| date issued | 2012 | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/3404280?locale-attribute=en | |
| description abstract | This paper presents a human gait recognition algorithm based on a leg gesture separation. Main innovation in this paper is gait recognition using leg gesture classification which is invariant to covariate conditions during walking sequence and just focuses on underbody motions and a neuro-fuzzy combiner classifier (NFCC) which derives a high precision recognition system. At the end, performance of the proposed algorithm has been validated by using the HumanID Gait Challenge data set (HGCD), the largest gait benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition, and time. And it has been compared to recent algorithm of gait recognition. | en |
| language | English | |
| title | Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method | en |
| journal title | ISRN Artificial Intelligence | fa |
| pages | 9-Jan | |
| journal volume | 2012 | |
| journal issue | 1 | |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1024451.html | |
| identifier articleid | 1024451 |