Detecting low-resolution faces in video

Neil Robertson; Nils Janssen

doi:10.1117/12.805984

19 January 2009 Detecting low-resolution faces in video

Neil Robertson, Nils Janssen

Proceedings Volume 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques; 725207 (2009) https://doi.org/10.1117/12.805984
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

This paper presents a method for the detection of faces (via skin regions) in images where faces may be low-resolution and no assumptions are made about fine facial features being visible. This type of data is challenging because changes in appearance of skin regions occur due to changes in both lighting and resolution. We present a non-parametric classification scheme based on a histogram similarity measure. By comparing performance of commonly-used colour-spaces we find that the YIQ colour space with 16 histogram bins (in both 1 and 2 dimensions) gives the most accurate performance over a wide range of imaging conditions for non-parametric skin classification. We demonstrate better performance of the non-parametric approach vs. colour thresholding and a Gaussian classifier. Face detection is subsequently achieved via a simple aspect-ratio and we show results from indoor and outdoor scenes.

Citation Download Citation

Neil Robertson and Nils Janssen "Detecting low-resolution faces in video", Proc. SPIE 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, 725207 (19 January 2009); https://doi.org/10.1117/12.805984

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KEYWORDS

Skin

Facial recognition systems

Databases

RGB color model

Light sources and illumination

Surveillance

Video surveillance

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