Real-Time Face Detection and Recognition in Complex Background
| Autor: | Xin Zhang, Jafar Saniie, Thomas Gonnot |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Face hallucination
Computer science Local binary patterns business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Pattern recognition 02 engineering and technology Facial recognition system Object-class detection ComputingMethodologies_PATTERNRECOGNITION Haar-like features Feature (computer vision) 0202 electrical engineering electronic engineering information engineering Three-dimensional face recognition 020201 artificial intelligence & image processing Computer vision Artificial intelligence Face detection business 021101 geological & geomatics engineering |
| Zdroj: | Journal of Signal and Information Processing. :99-112 |
| ISSN: | 2159-4481 2159-4465 |
| DOI: | 10.4236/jsip.2017.82007 |
| Popis: | This paper provides efficient and robust algorithms for real-time face detection and recognition in complex backgrounds. The algorithms are implemented using a series of signal processing methods including Ada Boost, cascade classifier, Local Binary Pattern (LBP), Haar-like feature, facial image pre-processing and Principal Component Analysis (PCA). The Ada Boost algorithm is implemented in a cascade classifier to train the face and eye detectors with robust detection accuracy. The LBP descriptor is utilized to extract facial features for fast face detection. The eye detection algorithm reduces the false face detection rate. The detected facial image is then processed to correct the orientation and increase the contrast, therefore, maintains high facial recognition accuracy. Finally, the PCA algorithm is used to recognize faces efficiently. Large databases with faces and non-faces images are used to train and validate face detection and facial recognition algorithms. The algorithms achieve an overall true-positive rate of 98.8% for face detection and 99.2% for correct facial recognition. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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