Authors:
Mazaher Karami
and
Alireza Ahmadyfard
Affiliation:
Department of Electronics, School of Robotics and Electronic Engineering, University of Technology, Iran, Islamic Republic of
Keyword(s):
Biometric, Frieze pattern, Gait recognition.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Feature Extraction
;
Features Extraction
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
Abstract:
In this paper, we address the problem of human identification using gait. Considering the recent work of Lee et al. (Lee et al., 2007) proposed for gait recognition. First we will introduce the algorithm proposed by Lee et al.. This method has two main steps: (1) extract key frames to define the gait cycle pattern, and (2) compute Shape Variation-based frieze patterns. These patterns are then used to classify and perform the gait identification. We modify the utilized features in this approach. We try to omit redundant features based on the effect of each feature on recognition rate and in next step, we improve performance of this approach by making some changes in way of feature extraction. Finally, we use the statistical characteristics of employed features instead of direct applying of remaining features. We test the proposed method on CASIA database. The experimental results are used to compare the proposed method with Lee et al. method.