Abstract
The problem of optimizing classifiers for object detection has already been discussed in several publications. In order to achieve better results, it was decided to use genetic algorithms to optimize the classifiers. By applying this approach optimization is automatic in respect to image (or group of images). For test issues the haar-like object detection features were used. Genetic model has been created over the field of solutions and evolved to provide better results. Proposed algorithm was tested and results are presented. The proposed solution can be applied to another type of classifier and adapted to optimize any detection parameter.
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Matiolański, A., Guzik, P. (2011). Automated Optimization of Object Detection Classifier Using Genetic Algorithm. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2011. Communications in Computer and Information Science, vol 149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21512-4_19
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DOI: https://doi.org/10.1007/978-3-642-21512-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21511-7
Online ISBN: 978-3-642-21512-4
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