Convolutional Neural Networks and Periocular Region Image Recognition
| Autor: | Eliana Pereira da Silva, Jose Hiroki Saito, Francisco Fambrini |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies Biometrics Computer science business.industry Competitive learning 0211 other engineering and technologies Neocognitron 02 engineering and technology Convolutional neural network Facial recognition system Face (geometry) 0202 electrical engineering electronic engineering information engineering Periocular Region 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | Communications in Computer and Information Science ISBN: 9783030638191 ICONIP (4) |
| DOI: | 10.1007/978-3-030-63820-7_36 |
| Popis: | There are some benefits in using periocular biometric traits for individual identification. This work describes the use of convolutional neural network Neocognitron, in this novel application, in individual recognition using periocular region images. Besides, it is used the competitive learning using the extreme points of lines detected in the preprocessing of the input images as winner positions. It was used Carnegie Mellon University - Pose, Illumination, and Expression Database (CMU-PIE), with 41,368 images of 68 persons. From these images, 57 \(\times \) 57 periocular images were obtained as training and test samples. The experiments indicate results in the Kappa index of 0.89, for periocular images, and 0.91 for complete face images. |
| Databáze: | OpenAIRE |
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