Face detection using beta wavelet filter and cascade classifier entrained with Adaboost

8 December 2015 Face detection using beta wavelet filter and cascade classifier entrained with Adaboost

Rim Afdhal, Akram Bahar, Ridha Ejbali, Mourad Zaied

Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 98750T (2015) https://doi.org/10.1117/12.2229620
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain

Abstract

Face detection has been one of the most studied topics in the computer vision literature due to its relevant role in applications such as video surveillance, human computer interface and face image database management. Here, we will present a face detection approach which contains two steps. The first step is training phase based on Adaboost algorithm. The second step is the detection phase. The proposed approach presents an enhancement of Viola and Jones’ algorithm by replacing Haar descriptors with Beta wavelet. The obtained results have proved an excellent performance of detection not only when a face is in front of the camera but also when it is oriented towards the right or the left. Moreover, thanks to the start period needed for the detection, our approach can be applied during a real time experience.

Citation Download Citation

Rim Afdhal, Akram Bahar, Ridha Ejbali, and Mourad Zaied "Face detection using beta wavelet filter and cascade classifier entrained with Adaboost", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98750T (8 December 2015); https://doi.org/10.1117/12.2229620

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