Research and Implementation of Pattern Recognition Based on Adaboost Algorithm

Pattern recognition and computer vision technology are long-term subjects of concern, which have high academic value and commercial value. Adaboost is an iterative algorithm, and its core idea is to obtain some weak classifier with a training set of training. Finally, a much stronger classifier is o...

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Veröffentlicht in:Sensors & transducers Jg. 159; H. 11; S. 7
Hauptverfasser: Chang, Luqun, Bian, Zhengfu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Toronto IFSA Publishing, S.L 01.11.2013
Schlagworte:
Accuracy
Algorithms
Classifiers
Detectors
Error correction & detection
Face recognition
Machine learning
Methods
Pattern recognition
Position (location)
Training
ISSN:2306-8515, 1726-5479, 1726-5479
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Zusammenfassung:Pattern recognition and computer vision technology are long-term subjects of concern, which have high academic value and commercial value. Adaboost is an iterative algorithm, and its core idea is to obtain some weak classifier with a training set of training. Finally, a much stronger classifier is obtained by combining weak classifiers. In this paper, the authors firstly introduce the basic theory of Adaboost algorithm, and then take face recognition as an application example. The training process and the detection process were achieved respectively and independently. Experimental results show the detector based on Adaboost algorithm can accurately detect the location of the face, regardless of their positions, scale, orientation, lighting conditions, expressions, etc., and it has a smaller detection error. Specifically, the detector can effectively detect multiple faces, and it also has much higher detection accuracy.
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ISSN:2306-8515
1726-5479
1726-5479