Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images

Iris centre localization in low-resolution visible images is a challenging problem in computer vision community due to noise, shadows, occlusions, pose variations, eye blinks, etc. This paper proposes an efficient method for determining iris centre in low-resolution images in the visible spectrum. Even low-cost consumer-grade webcams can be used for gaze tracking without any additional hardware. A two-stage algorithm is proposed for iris centre localization. The proposed method uses geometrical characteristics of the eye. In the first stage, a fast convolution based approach is used for obtaining the coarse location of iris centre (IC). The IC location is further refined in the second stage using boundary tracing and ellipse fitting. The algorithm has been evaluated in public databases like BioID, Gi4E and is found to outperform the state of the art methods.Comment: 12 pages, 10 figures, IET Computer Vision, 201

Separability Filter for Localizing Abnormal Pupil: Identification of Input Image

 Separability filter method is a reliable method for pupil detection. However, so far this method is implemented for detecting pupil of normal eye, while for abnormal eye such as cataract and glaucoma patients; they have different characteristics of pupil such as color, shape and radius size of pupil. In this paper we propose to use separability filter for detecting pupil of abnormal patients with different characteristics. We faced a problem about radius size, shape and color of pupil; therefore we implemented Hough Transform, Blob area and Brightness for identifying input images before applying separability filter. The experiment results show that we can increase performance of pupil detection for abnormal eye to be 95.65%

Detecting the Eyes and their Parts in Video Sequences

Import 22/07/2015Tato diplomová práce se zaměřuje na navržení metod a vytvoření softwaru pro detekci očních částí v obrázcích získaných kamerou. Konkrétně se jedná o nalezení očních oblastí, detekce duhovky, detekce zornice a nalezení očních víček. Obrázky se kterými software pracuje jsou ve stupních šedi a byly pořízeny za běžného, případně infračerveného osvětlení. Motivací pro tuto práci bylo předpokládané použití detekce v systému pro sledování řidiče a míry jeho unavenosti, a prací tak přispět ke zvýšení bezpečnosti na cestách a dálnicích. V textu popisuji metody, které jsou již známé, dále metody, které jsem modifikoval a i metody, které jsem sám navrhl. Výsledkem této diplomové práce je implementace detekce očních částí v jazyce C++, podrobný popis použitých technik a detailní experimentální část, ve které je vyhodnocena úspěšnost a časová náročnost na více než 1 500 obrázcích.The thesis is focused on designing the methods and creating the software for detecting different parts of eyes in the images taken by a camera. This is done by finding the specific area of eye, which is followed by detecting the iris, locating the pupil, and identifying the eye lids. The system works with the grayscale images that can be taken using both natural and infrared light. My primary motivation for choosing this topic was the anticipated use of this detection system for monitoring the drivers and measuring their drowsiness while they are driving. This should help to increase the safety on roads and motorways. In my work, I describe the methods that are already known, as well as the methods I have modified, and the methods that were created by myself. The final practical outcome of this diploma thesis is the implementation of the methods that can recognize various parts of eye. The implementation is done in C++. The work also includes a detailed description of the techniques that were used. It also contains a thorough experimental evaluation including efficiency and time complexity, which was evaluated for over 1500 images.460 - Katedra informatikyvýborn