Camera-based eye blinks pattern detection for intelligent mouse (original) (raw)
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Eye-blink detection system for human–computer interaction
Universal Access in the Information Society, 2012
A vision-based human-computer interface is presented in the paper. The interface detects voluntary eyeblinks and interprets them as control commands. The employed image processing methods include Haar-like features for automatic face detection, and template matching based eye tracking and eye-blink detection. Interface performance was tested by 49 users (of which 12 were with physical disabilities). Test results indicate interface usefulness in offering an alternative mean of communication with computers. The users entered English and Polish text (with average time of less than 12s per character) and were able to browse the Internet. The interface is based on a notebook equipped with a typical web camera and requires no extra light sources. The interface application is available on-line as open-source software.
Blink detection for real-time eye tracking
Journal of Network and Computer Applications, 2002
This work is motivated by our goal of providing non-contact head and eye based control of computer systems for people with motor difficulties. The system described here uses spatio-temporal filtering and variance maps to locate the head and find the eye-feature points respectively. These feature points are accurately tracked in the succeeding frames by using a modified version of the Lucas-Kanade tracking algorithm with pyramidal implementation. Accurate head and eye tracking results are obtained at a processing rate of more than 30 fps in more than 90% cases with a low false positive blink detection rate of 0.01%. This is achieved under varying lighting conditions for people of different ethnicity, with and without wearing glasses.
Adaptive Real Time Eye-Blink Detection System
The eye is one of the sense organs that can give users better interaction closer to their need by observing the change of the eyes (open or closed). It is considered as a rich source for gathering information on our daily life. So, it is used in computer science area, especially in human computer interaction. This paper proposes a new system for detecting eye blinks accurately without any restriction on the background and the user does not have to wear any sensors or marks. No manual initialization is required in our proposed system. The proposed system works with the online and offline environment. It automatically classifies the eye as either open or closed at each video frame. The proposed system is tested with the users who wear glasses and the experiments proved its applicability. The proposed system is very easy to configure and use. It is totally non-intrusive and it only requires one low-cost web camera and computer.
2012
In recent years, there has been an increased interest and effort to augment traditional human-computer interfaces like the keyboard and mouse with intelligent interfaces that allow users to interact with the computer more naturally and effectively. Such systems are particularly important for elderly and physically challenged persons. In this work the primary goal is to develop a computer vision system that make computers to perceptive a user’s natural communicative signals such as voluntary eye blinks and interpretation of blink patterns for communication between man and machine. The traditional human-computer interfaces demand good manual agility and refined motor control, which may be absent or unpredictable for people with certain disabilities. Here it is proposed robust, accurate algorithms to detect eyes and measure the duration of blinks, and interpret them in real time to control a nonintrusive human-computer interface. The complete system is divided into two primary major mo...
Eye-Blink Detection System for Virtual Keyboard
This paper is about Human-Computer Interaction (HCI). It focuses on the interface and interaction between people and computers. The main goal of the HCI is to design machinery that lets people interact with computers in a novel way. This is very useful for people who are physically challenged as they can interact and surf the internet. An eyeblink is used in this system to enter special characters and alphabets similar to when a user enters it manually on a keyboard instead of the user entering it by blinking an eye. The most substantial method people use to interact is eye blinking and eye movement for people with physical disabilities.
Communication via eye blinks and eyebrow raises: video-based human-computer interfaces
Two video-based human-computer interaction tools are introduced that can activate a binary switch and issue a selection command. "BlinkLink," as the first tool is called, automatically detects a user's eye blinks and accurately measures their durations. The system is intended to provide an alternate input modality to allow people with severe disabilities to access a computer. Voluntary long blinks trigger mouse clicks, while involuntary short blinks are ignored. The system enables communication using "blink patterns:" sequences of long and short blinks which are interpreted as semiotic messages. The second tool, "EyebrowClicker," automatically detects when a user raises his or her eyebrows and then triggers a mouse click. Both systems can initialize themselves, track the eyes at frame rate, and recover in the event of errors. No special lighting is required. The systems have been tested with interactive games and a spelling program. Results demonstrate overall detection accuracy of 95.6% for BlinkLink and 89.0% for Eye-browClicker.
IJERT-Eye Blink Detection Method for disabled: Assisting System for Paralyzed
International Journal of Engineering Research and Technology (IJERT), 2020
https://www.ijert.org/eye-blink-detection-method-for-disabled-assisting-system-for-paralyzed https://www.ijert.org/research/eye-blink-detection-method-for-disabled-assisting-system-for-paralyzed-IJERTCONV8IS15035.pdf We represent a real time method based on some video and image processing algorithms for eye blink detection. The motivation of this research is the need of disabling who cannot communicate with human. A Haar Cascade Classifier is applied for face and eye detection for getting eye and facial axis information. In addition, the same classifier is used based on Haar-like features to find out the relationship between the eyes and the facial axis for positioning the eyes. An efficient eye tracking method is proposed which uses the position of detected face. Finally, an eye blinking detection based on eyelids state (close or open) is used for controlling android mobile phones. The method is used with and without smoothing filter to show the improvement of detection accuracy. The application is used in real time for studying the effect of light and distance between the eyes and the mobile device in order to evaluate the accuracy detection and overall accuracy of the system. Test results show that our proposed method provides a 98% overall accuracy and 100% detection accuracy for a distance of 35 cm and an artificial light.
EOG Based Eye Blink Detection using VB GUI for Eye Writing Applications
International Journal of Computer Science and Mobile Computing
Usage of bio-signals from Electro-Oculo-Gram (EOG) in Human Computer Interaction (HCI) systems is one of the burgeoning study areas as of now. In order to provide support for physically challenged persons (or keypad Contactless HCI) in operating basic computer functions without making any physical touch with the computer keypad or mouse, we propose a framework utilization concept that changes movement of cursor on the computer screen using virtual keypad based on Visual Basic Graphical User Interface (VB GUI) with the eye movement detection through webcam of the system for different computer functions. In this work, VB GUI platform is used for a web browsing application and corresponding platform operation steps have been included. With the VB GUI, the basic cursor movements in the directions of left, right, up, and down to access the web links on the web page which is treated as eye writing in the concept of human computer interaction. Similarly, we can access different computer Ap...
Real-time eye blink and wink detection for object selection in HCI systems
Journal on Multimodal User Interfaces, 2018
This paper presents an approach for real-time detection of three types of eye blinks: eye blink (blinking both eyes simultaneously), left and right winks. The process of blink detection has been divided into four parts viz. face localization in facial images acquired through a video camera, eye pair localization, pixels' motion analysis using optical flow technique, and classification of eye blinks. Blink detection has been performed using a video camera and MATLAB software with image processing and computer vision toolbox. The algorithm takes about 60 ms time for processing a frame and 250 ms time for confirmation and classification of the detected blink. An experiment was conducted to evaluate the performance of the proposed approach in which 10 users voluntarily participated. The performance of the proposed method has been tested under two lighting conditions: natural lighting conditions and controlled lighting conditions. Also, the performance has been tested by varying the distance of the user from the camera. Here, it is observed that the system gives best performance when used under controlled lighting conditions and the user sitting at a distance of about 0.5 m. Accuracy of the proposed approach has been found to be 96, 92 and 88% for detection of eye blink, left wink and right wink, respectively. The proposed method has also been tested on ZJU dataset where it has given precision, detection accuracy and false alarm rate of values 94.11, 91.2 and 1.54%, respectively. The proposed system has been used and evaluated for performing various mouse analogous functions using eye blinks and winks. It has given an accuracy of 90, 80 and 90% in performing left click, double click, and right click operations, respectively. Keywords Real-time eye blink detection • Target selection • Analogous mouse operations • HCI systems 1 Introduction Eye blink detection is used in different applications e.g. object selection in HCI systems [1], driver fatigue detection [2,3], or liveness detection [4]. Object selection is a very significant part of a human-computer interaction system. Two commonly used selection triggers are the key trigger, where
Automated eye blink detection and tracking using template matching
2013 IEEE Student Conference on Research and Developement, 2013
This paper presents comparison of two image processing algorithms used for eye blink detection. The motivation of this research work is the need of disabled persons who are unable to move their body parts except eyes. The process of blink detection is divided into three parts viz.face localization, eye pair localization and template matching method. In method 1, YCbCr color model and morphological operations are used for the face and eyes localization. In method 2 face and eyes pair localization is performed by using Viola Jones method. After eye pair localization, the concept of template matching is applied for blink detection, in both the methods. A performance comparison is made for both the methods based upon detection accuracy and processing time. It is observed that method 1, gives better accuracy (80.75%) with low processing time (0.38sec.). The overall success rate of method 1 and method 2 is 71% and55% respectively.