Histogram of weighted local directions for gait recognition

Sivapalan, Sabesan, Chen, Daniel, Denman, Simon, Sridharan, Sridha, & Fookes, Clinton B. (2013) Histogram of weighted local directions for gait recognition. In Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, Oregon Convention Center, Portland, OR, pp. 125-130.

View at publisher


In this paper, we explore the effectiveness of patch-based gradient feature extraction methods when applied to appearance-based gait recognition. Extending existing popular feature extraction methods such as HOG and LDP, we propose a novel technique which we term the Histogram of Weighted Local Directions (HWLD). These 3 methods are applied to gait recognition using the GEI feature, with classification performed using SRC. Evaluations on the CASIA and OULP datasets show significant improvements using these patch-based methods over existing implementations, with the proposed method achieving the highest recognition rate for the respective datasets. In addition, the HWLD can easily be extended to 3D, which we demonstrate using the GEV feature on the DGD dataset, observing improvements in performance.

Impact and interest:

7 citations in Scopus
Search Google Scholar™
6 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

87 since deposited on 25 Sep 2013
14 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 62889
Item Type: Conference Paper
Refereed: Yes
Keywords: Gait energy image, HOG, MDA, PCA, LDP, GEV, SRC
DOI: 10.1109/CVPRW.2013.26
ISBN: 9780769549903
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Deposited On: 25 Sep 2013 23:11
Last Modified: 09 Oct 2013 23:54

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page