An Efficient HOG-Centroid Descriptor for Human Gait Recognition
- Title
- An Efficient HOG-Centroid Descriptor for Human Gait Recognition
- Creator
- Sugandhi K.; Raju G.
- Description
- Automatic recognition of human gait have gained much attention nowadays. Histogram of Oriented Gradient (HOG) is a widely adopted descriptor for object's shape analysis. In this paper, combination of HOG descriptor with silhouette centroid for human gait recognition is proposed. The resultant descriptor, namely HOG-Centroid, achieves better recognition performance on comparison with HOG descriptor individually as well as other existing gait recognition methods. Experiments are carried out with CASIA gait dataset B and cumulative matching scores of 95.3%, 98.1% and 99.2% are obtained for rank 1, rank 5 and rank 10 respectively. 2019 IEEE.
- Source
- Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019, pp. 355-360.
- Date
- 2019-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Centroid; Descriptor; Feature fusion; Gait; HOG; Silhouette
- Coverage
- Sugandhi K., Department of Information Technology, Kannur University, Kannur, Kerala, 670567, India; Raju G., Department of CSE, Christ (Deemed to Be University), Bengaluru, Karnataka, 560764, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-153869346-9
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sugandhi K.; Raju G., “An Efficient HOG-Centroid Descriptor for Human Gait Recognition,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20788.