Face detection at a distance with AdaBoost filtering and color-shape information

Seokwon Yeom; Dong-Su Lee

doi:10.1117/12.2015350

28 May 2013 Face detection at a distance with AdaBoost filtering and color-shape information

Seokwon Yeom, Dong-Su Lee

Proceedings Volume 8755, Mobile Multimedia/Image Processing, Security, and Applications 2013; 87550I (2013) https://doi.org/10.1117/12.2015350
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Face detection at a distance is very challenging because the image quality becomes low. This paper discusses a face detection method in the long distance with AdaBoost filtering and a false alarm reduction scheme. The false alarm reduction scheme is based on skin-color testing and variable edge mask filtering. The skin-color test involves the average RGB components of the window, followed by the binary cluster image generation. The binary cluster is composed of the alternative and null pixels according to color. The size of the edge mask is determined by the ellipse covering the binary cluster. The edge mask filters out false alarms by evaluating the contour shape of the object in the window. In the experiments, the false alarm reduction scheme is shown to be effective for face detection in images captured at a distance.

Citation Download Citation

Seokwon Yeom and Dong-Su Lee "Face detection at a distance with AdaBoost filtering and color-shape information", Proc. SPIE 8755, Mobile Multimedia/Image Processing, Security, and Applications 2013, 87550I (28 May 2013); https://doi.org/10.1117/12.2015350

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