Ahmed El-Barkouky

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Faces in the wild have recently captured the focus of researchers for all facial analysis problems. Partial occlusion is a major problem for analyzing faces captured in unconstrained non-cooperative conditions. Even detecting the faces in such conditions is a challenging problem that needs to be solved before any further analysis of such faces can be done.(More)
Face and eye detection algorithms are deployed in a wide variety of applications. Unfortunately, there has been no quantitative comparison of how these detectors perform un­ der difficult circumstances. We created a dataset of low light and long distance images which possess some of the problems encountered by face and eye detectors solving real world(More)
Recently, several approaches for pedestrian detection have been investigated using discriminatively trained part based models with which Histogram of Oriented Gradients (HOG) showed to be a robust feature. In this paper, we propose a new feature based on HOG to be used with the discriminatively trained part framework for pedestrian detection. Our method is(More)
Face detection has been one of the most studied topics in the biometrics literature. A critical factor in the face detection process is the complexity of the setup used to acquire the images. The face detection might be considered a solved problem in easy setups but for outdoor setups with unconstrained illumination and background conditions the problem is(More)
Face detection and Facial feature extraction are considered among the most studied topics in the field of biometrics. In real-world uncontrolled scenarios, high rate of false alarm is still a major problem. This paper presents a solution to reduce false alarm rate resulting from any generic face detector, through a fast post-processing algorithm based on(More)
Pedestrian detection is an important problem in the design of driving assistance systems that can reduce accidents and save lives. Although many annotated visible pedestrian datasets are publically available, similar annotated thermal datasets are rare. Such datasets are essential for training a classifier that can be used for pedestrian detection at night(More)
In this paper, we propose a thermal image based measurement technique for the volumetric flow rate of a liquid inside a thin tube. Our technique makes use of the convection heat transfer dependency between the flow rate and the temperature of the flowing liquid along the tube. The proposed method can be applied to diagnose superficial venous disease(More)
In this paper we propose an educational robotic system for teaching kids at nursery schools how to write and draw simple shapes. Our system uses the humanoid robot NAO to draw shapes appearing on a computer screen. The system uses light polarization property for fast detection of the screen despite of its content. We also propose a mapping from the image(More)
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