Inter Frame Statistical Feature Fusion for Human Gait Recognition
- Title
- Inter Frame Statistical Feature Fusion for Human Gait Recognition
- Creator
- Sugandhi K.; Wahid F.F.; Raju G.
- Description
- Researches showed that gait is unique for individuals and human gait recognition gained much attention nowadays. The sequence of gait silhouettes extracted from the video sequences has its own significance for gait recognition performance. In this paper, a novel inter frame feature discriminating the individual gait characteristics is proposed. Consecutive frames within a gait cycle are divided into equal number of blocks and corresponding block differences are calculated. It can preserve the minute temporal variations of the different body parts within each block and the cumulative difference provide a unique feature capable of discriminating individuals. To avoid synchronization problems, secondary statistical features are extracted from the primary inter frame variations. Finally, feature level fusion schemes are applied on these statistical features with existing features extracted from CEI representation. The efficiency of the proposed feature is evaluated on widely adopted CASIA gait dataset B using subspace discriminant analysis. The experimental results show that our proposed feature has better recognition accuracy in comparison with existing features. 2019 IEEE.
- Source
- 2019 International Conference on Data Science and Communication, IconDSC 2019
- Date
- 2019-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Feature fusion; Gait; Inter frame; Silhouette
- Coverage
- Sugandhi K., Department of Information Technology, Kannur University, Kannur, Kerala, India; Wahid F.F., Department of Information Technology, Kannur University, Kannur, Kerala, India; Raju G., Department of CSE, Faculty of Engineering, Christ, Deemed to be University, Bengaluru, Karnataka, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-153869319-3
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sugandhi K.; Wahid F.F.; Raju G., “Inter Frame Statistical Feature Fusion for Human Gait Recognition,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20772.