Title : ( Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method )
Authors: Hadi Sadoghi Yazdi , Hessam Jahani Fariman , Jaber Roohi ,
Full TextAbstract
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.
Keywords
, Gait Recognition Based on Invariant Leg Classification Using a Neuro, Fuzzy Algorithm as the Fusion Method
@article{paperid:1024451,
author = {Sadoghi Yazdi, Hadi and Jahani Fariman, Hessam and Jaber Roohi},
title = {Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method},
journal = {ISRN Artificial Intelligence},
year = {2012},
volume = {2012},
number = {1},
month = {March},
issn = {2090-7435},
pages = {1--9},
numpages = {8},
keywords = {Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method},
}
%0 Journal Article
%T Gait Recognition Based on Invariant Leg Classification Using a Neuro-Fuzzy Algorithm as the Fusion Method
%A Sadoghi Yazdi, Hadi
%A Jahani Fariman, Hessam
%A Jaber Roohi
%J ISRN Artificial Intelligence
%@ 2090-7435
%D 2012
