DocumentCode :
3285613
Title :
Learnt combination in object detector ensembles
Author :
Neugebauer, Christopher ; Cameron-Jones, Mike ; Horton, Michael
Author_Institution :
Sch. of Comput. & Inf. Syst., Univ. of Tasmania, Hobart, TAS, Australia
fYear :
2010
fDate :
8-9 Nov. 2010
Firstpage :
1
Lastpage :
8
Abstract :
This paper considers the application of meta-classification techniques to the task of object detection. The technique of learnt combination is presented and evaluated in the domain of face detection: in the case of an ensemble of greyscale detectors it is shown to be as effective as pre-existing ensemble detection techniques. It is shown that considering detectors operating on different colour channels can improve performance; to exploit this, a method for selecting appropriate colour channels is also presented. Also presented is a new data set for training and evaluating colour-based face detectors.
Keywords :
face recognition; learning (artificial intelligence); object detection; pattern classification; colour channels; face detection; greyscale detectors; learnt combination; meta-classification techniques; object detection; object detector ensembles; Detectors; Educational institutions; Face; Logistics; Materials; Merging; Training; Object detection; ensemble classification; face detection; meta-classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Vision Computing New Zealand (IVCNZ), 2010 25th International Conference of
Conference_Location :
Queenstown
ISSN :
2151-2191
Print_ISBN :
978-1-4244-9629-7
Type :
conf
DOI :
10.1109/IVCNZ.2010.6148791
Filename :
6148791
Link To Document :
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