Multi-class AdaBoost learning of facial feature selection through grid computing

2010 IEEE 9th International Conference on Cybernetic Intelligent Systems, CIS 2010

Volumn , Issue , 2010, Pages

  Zhou, Mian ^a,b,c   Wei, Hong ^b   Bland, Ian ^b   Worrall, Anthony ^b   Spence, David ^b   Wang, Xiangjun ^a   Wen, Pengcheng ^a   Liu, Feng ^a  

^a TIANJIN UNIVERSITY   (China)

^b UNIVERSITY OF READING   (United Kingdom)

^c TIANJIN FOREIGN STUDIES UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADABOOST LEARNING; COMPUTATIONAL TIME; EFFICIENT METHOD; FACIAL FEATURE SELECTION; FEATURE TRANSFORMATIONS; GRID COMPUTING SYSTEMS; HIGH PERFORMANCE COMPUTING; HIGH-THROUGHPUT COMPUTING; LEARNING PROCESS; LONG DURATION; MULTI-CLASS; MULTIPLE CLASSIFIERS; OBJECT DETECTION; OFF-LINE LEARNING; PARALLEL STRUCTURES; RESOURCE MANAGEMENT; SELECTION ALGORITHM;

ADAPTIVE BOOSTING; ALGORITHMS; COMPUTER SOFTWARE SELECTION AND EVALUATION; COMPUTER VISION; FACE RECOGNITION; FEATURE EXTRACTION; IMAGE RESOLUTION; INTELLIGENT SYSTEMS; OBJECT RECOGNITION; THROUGHPUT;

GRID COMPUTING;

EID: 79960364590     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/UKRICIS.2010.5898149     Document Type: Conference Paper

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