MapReduce Implementation of Face Recognition Based on HOG Feature and NSMD
| Autor: | Shi Zhao Li, Hao Feng Huang, Nan Feng Xiao |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Computer science
business.industry Mode (statistics) Boundary (topology) Sample (statistics) Pattern recognition General Medicine Machine learning computer.software_genre Facial recognition system Identification (information) Hyperplane Simple (abstract algebra) Feature (machine learning) Artificial intelligence business computer |
| Zdroj: | Applied Mechanics and Materials. :1572-1575 |
| ISSN: | 1662-7482 |
| Popis: | There are some problems in the traditional face recognition: too sensitive to light, its classification is too simple, hard to apply to distributed system. For these problems, this paper does three work: used HOG feature in the face recognition, that improved it get more steady feature in different type of light; putting forward NSMD (Nearest Sample Max Distance), it try to find some partly best classifications to unite one strong classification, so the classification hyperplane can be more far from the sample boundary; finally the algorithms of this paper specially the one-to-one design mode are adapt to MapReduce, so its feasible to own the advantages of distributed system (expansively safety...). With the experiment analysis, the work gets their goals: HOG feature can be adapt to different lights, NSMD can get better rate of identification, the MapReduce algorithms can get fine speed-up ratio. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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