Spindle Net: Person Re-identification with Human Body Region Guided Feature Decomposition and Fusion
Group Sense (China) · Chinese University of Hong Kong
Abstract
Person re-identification (ReID) is an important task in video surveillance and has various applications. It is non-trivial due to complex background clutters, varying illumination conditions, and uncontrollable camera settings. Moreover, the person body misalignment caused by detectors or pose variations is sometimes too severe for feature matching across images. In this study, we propose a novel Convolutional Neural Network (CNN), called Spindle Net, based on human body region guided multi-stage feature decomposition and tree-structured competitive feature fusion. It is the first time human body structure information is considered in a CNN framework to facilitate feature learning. The proposed Spindle Net…
Citation impact
- FWCI
- 47.32
- Percentile
- 100%
- References
- 40
Authors
8Topics & keywords
- Computer science
- Discriminative model
- Artificial intelligence
- Robustness (evolution)
- Feature (linguistics)
- Pattern recognition (psychology)
- Feature extraction
- Convolutional neural network
- Reduced inequalities