An Efficient Characterization of Gait for Human Identification

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Mridul Ghosh 1,* Debotosh Bhattacharjee 2

1. Department of Computer Science and Engineering, Seacom Engineering College, Howrah,India

2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

* Corresponding author.


Received: 21 Feb. 2014 / Revised: 28 Mar. 2014 / Accepted: 7 May 2014 / Published: 8 Jun. 2014

Index Terms

Gait Recognition, corner points, centroid, LRFG, ABLC, DBCC, Mahalanobis Distance


In this work, a simple characterization of human gait, which can be used for surveillance purpose, is presented. Different measures, like leg rise from ground (LRFG), the angles created between the legs with the centroid (ABLC), the distances between the control points and centroid (DBCC) have been taken as different features. In this method, the corner points from the edge of the object in the image have been considered. Out of several corner points thus extracted, a set of eleven significant points, termed as control points, that effectively and rightly characterize the gait pattern, have been selected. The boundary of the object has been considered and using control points on the boundary the centroid of those has been found out. Statistical approach has been used for recognition of individuals based on the n feature vectors, each of size 23(collected from LRFG, ABLCs, and DBCCs) for each video frame, where n is the number of video frames in each gait cycles. It has been found that recognition result of our approach is encouraging with compared to other recent methods.

Cite This Paper

Mridul Ghosh, Debotosh Bhattacharjee,"An Efficient characterization of Gait for Human Identification", IJIGSP, vol.6, no.7, pp.19-27, 2014. DOI: 10.5815/ijigsp.2014.07.03


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