Gait recognition based on gait pal and pal entropy image

M Jeevan, Neha Jain, M. Hanmandlu, Girija CHETTY

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

59 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings 20th 2013 IEEE International Conference on Image Processsing (ICIP 2013)
EditorsDavid Taudman, Min Wu
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781479923410
Publication statusPublished - 15 Sept 2013
Event2013 IEEE International Conference on Image Processing ICIP2013 - Melbourne, Melbourne, Australia
Duration: 5 Sept 201318 Sept 2013


Conference2013 IEEE International Conference on Image Processing ICIP2013


Dive into the research topics of 'Gait recognition based on gait pal and pal entropy image'. Together they form a unique fingerprint.

Cite this