Abdulaziz Abdullah Alorf, A. Lynn Abbott


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.

Abdulaziz Alorf, A. Lynn Abbott: Improved Face and Head Detection Based on Traditional Middle Eastern Clothing. ICIAR 2017: 389-398


A. Lynn Abbott

Publication Details

Date of publication:
June 2, 2017
International Conference on Image Analysis and Recognition
Page number(s):