TY - GEN
T1 - Gait recognition based on gait pal and pal entropy image
AU - Jeevan, M.
AU - Jain, Neha
AU - Hanmandlu, M.
AU - Chetty, Girija
PY - 2013
Y1 - 2013
N2 - Human Gait recognition is one of the most promising research areas at the moment. Gait is the style or manner of walking on foot. Gait recognition aims to identify individuals by the manner in which they walk. Existing Gait representations which capture both motion and appearance information are sensitive to changes in various covariate conditions such as carrying and clothing. In this paper, we propose a novel temporal representation of Gait using Pal and Pal Entropy (GPPE) for each cycle of the silhouettes. The Principal component analysis is applied to each of the features extracted to create a feature matrix. Support Vector Machine (SVM) is used for training and testing of individuals by the proposed method. Extensive experiments on the Treadmill dataset and the CASIA datasets A, B, C have been carried out to demonstrate the effectiveness of the proposed representation of Gait.
AB - Human Gait recognition is one of the most promising research areas at the moment. Gait is the style or manner of walking on foot. Gait recognition aims to identify individuals by the manner in which they walk. Existing Gait representations which capture both motion and appearance information are sensitive to changes in various covariate conditions such as carrying and clothing. In this paper, we propose a novel temporal representation of Gait using Pal and Pal Entropy (GPPE) for each cycle of the silhouettes. The Principal component analysis is applied to each of the features extracted to create a feature matrix. Support Vector Machine (SVM) is used for training and testing of individuals by the proposed method. Extensive experiments on the Treadmill dataset and the CASIA datasets A, B, C have been carried out to demonstrate the effectiveness of the proposed representation of Gait.
UR - http://www.scopus.com/inward/record.url?scp=84897818281&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897818281&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2013.6738864
DO - 10.1109/ICIP.2013.6738864
M3 - Conference contribution
AN - SCOPUS:84897818281
SN - 9781479923410
T3 - 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
SP - 4195
EP - 4199
BT - 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
PB - IEEE Computer Society
T2 - 2013 20th IEEE International Conference on Image Processing, ICIP 2013
Y2 - 15 September 2013 through 18 September 2013
ER -