Unconstrained Face Recognition using Bayesian Classification
| Autor: | A. Vinay, K. N. Balasubramanya Murthy, Aprameya Bharadwaj, Abhijay Gupta, S Natarajan, Arvind Srinivasan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science 05 social sciences ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Word error rate Pattern recognition 02 engineering and technology Facial recognition system 050105 experimental psychology Naive Bayes classifier 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Affine transformation Artificial intelligence Invariant (mathematics) business General Environmental Science |
| Zdroj: | Procedia Computer Science. 143:519-527 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2018.10.425 |
| Popis: | In this paper we propose a method for person identification. The proposed method is invariant to illumination, scale, pose, camera exposure and translation of the head. In order to make the model illumination invariant, a linear transform is applied. Binary affine features are used to extract facial features from each image. The facial features obtained are compressed to form a vector which is then passed to a Bayesian classifier. This method was tested on three benchmark datasets to show as to how the method overcomes of all the hurdles such as variation of illumination, change of scale, motion of head, change in expression and more. The error rate obtained is in the neighbourhood of 18%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|