Knowledge Transfer for Face Verification Using Heterogeneous Generalized Operational Perceptrons
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Image Processing (ICIP) |
| Publisher | IEEE |
| Pages | 1168-1172 |
| Number of pages | 5 |
| ISBN (Electronic) | 978-1-5386-6249-6 |
| ISBN (Print) | 978-1-5386-6250-2 |
| DOIs | |
| Publication status | Published - Sep 2019 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE International Conference on Image Processing - Duration: 1 Jan 1900 → … |
Publication series
| Name | IEEE International Conference on Image Processing |
|---|---|
| ISSN (Print) | 1522-4880 |
| ISSN (Electronic) | 2381-8549 |
Conference
| Conference | IEEE International Conference on Image Processing |
|---|---|
| Period | 1/01/00 → … |
Abstract
Face verification is a prominent biometric technique for identity authentication that has been used extensively in several security applications. In practice, face verification is often performed along with other visual surveillance tasks in the computing device. Thus, the ability to share the computation and reuse the information already extracted for other analysis tasks can greatly help reduce the computation load on the devices. In this study, we propose to utilize the knowledge transfer approach for the face verification problem by building a heterogeneous neural network architecture of Generalized Operational Perceptrons on top of the intermediate features extracted for object recognition purpose. Experimental results show that using our proposed approach, a face verification system can be incorporated into an existing visual analysis system with less additional memory and computational cost, compared to other similar approaches.
Keywords
- Face, Visualization, Feature extraction, Neurons, Network architecture, Face recognition, Surveillance, Face Verification, Generalized Operational Perceptron, Progressive Neural Network Learning