A complete person re-identification model using Kernel-PCA-based Gabor-filtered hybrid descriptors
- Title
- A complete person re-identification model using Kernel-PCA-based Gabor-filtered hybrid descriptors
- Creator
- Sathish P.K.; Balaji S.
- Description
- Person re-identification is a challenging problem in computer vision. Lots of research interest is observed in this area over the past few years. A model for complete person re-identification can prove useful in this direction. Use of convolutional neural networks for pedestrian detection can improve the accuracy of detection to a larger extent. Deriving a descriptor which is invariant to the changes in the illumination, background and the pose can make the difference in the re-identification process. The predominant part of our work focuses on building a robust descriptor which can tackle such challenges. We have concentrated on building a descriptor by employing appearance-based features extracted both at local and global levels. Further, the dimensionality of the descriptor is reduced using kernel PCA. Distance metric learning algorithms are used to evaluate the descriptor on three major benchmark datasets. We propose a complete person re-identification system which involves both pedestrian detection and person re-identification. Major contributions of this work are to detect pedestrians from surveillance videos using CNN-based learning and to generate a kernel-PCA-based spatial descriptor and evaluate the descriptor using known distance metric learning methods on benchmark datasets. 2018, Springer-Verlag London Ltd., part of Springer Nature.
- Source
- International Journal of Multimedia Information Retrieval, Vol-7, No. 4, pp. 221-229.
- Date
- 2018-01-01
- Publisher
- Springer London
- Subject
- Deep learning; Distance metric learning; Kernel PCA; Pedestrian detection; Person re-identification; Spatial descriptor; Video surveillance
- Coverage
- Sathish P.K., Department of Computer Science and Engineering, Christ University, Bengaluru, 560074, India; Balaji S., Centre for Incubation, Innovation, Research and Consultancy, Jyothi Institute of Technology, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 21926611
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Sathish P.K.; Balaji S., “A complete person re-identification model using Kernel-PCA-based Gabor-filtered hybrid descriptors,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 1, 2025, https://archives.christuniversity.in/items/show/16860.