Improved Face and Head Detection Based on Traditional Middle Eastern Clothing

This paper is concerned with the detection of individuals in images who wear traditional Middle Eastern clothing. Traditional headwear for men includes a scarf known as the shemagh that often occludes the face or causes significant shadows. State-of-the-art face-detection systems do not perform well for these cases. To address this problem, we have developed a novel approach that detects a distinctive part of traditional headwear known as the igal. This is a band or cord, typically black, that rests on the shemagh to hold it in place. Our approach starts by applying multiscale SVM classification with a HoG descriptor to perform tentative detection. The proposed detections are then refined using a bag of visual words categorization system. Experimental results have shown significantly better performance for our technique over several face-detection systems. Our technique yielded an F1 score of 80% with a low false-positive rate, showing an improvement of 15% over the best face detector.