Gait tracking and recognition by SIFT and type-2 fuzzy logic

Author

Djelal, N. ; Saadia, Nadia ; Ramdane-Cherif, Amar

Author_Institution

Lab. of Robot., Parallelism & Electroenergetics, Univ. of Sci. & Technol. Houari Boumediene, Algeries, Algeria

Volume

01

fYear

2013

fDate

16-18 Dec. 2013

Firstpage

138

Lastpage

142

Abstract

In the present study we intend to develop gait models through the Scale-Invariant Feature Transform algorithm (SIFT) so as to get the dynamic behavior of the gait and using it as a robust descriptor towards the scale variation and the rotation of the image. This descriptor is used by the type-2 fuzzy logic in order to classify the normal and abnormal gaits. The validation of the models was carried out via our data base the USF dataset. The outcomes of this work are more accurate in comparison with other methods.

Keywords

computer vision; fuzzy logic; fuzzy set theory; gait analysis; image motion analysis; medical image processing; object recognition; object tracking; transforms; SIFT; USF dataset; abnormal gait classification; gait dynamic behavior; gait model; gait recognition; gait tracking; image rotation; scale variation; scale-invariant feature transform algorithm; type-2 fuzzy logic; Classification algorithms; Feature extraction; Fuzzy logic; Gait recognition; Hidden Markov models; Transforms; Uncertainty; Gait tracking; SIFT descriptor; gait recognition; training; type-2 fuzzy Logic;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2013 6th International Congress on

Conference_Location

Hangzhou

Print_ISBN

978-1-4799-2763-0

Type

conf

DOI

10.1109/CISP.2013.6743973

Filename

6743973