11-02-2012, 11:59 AM
BLUE EYES TECHNOLOGY
ABSTRACT:
This paper mainly deals about how humans can interact directly with the computer. Blue Eyes technology is one amongst the many upcoming innovations done to the world of technology and there is no wonder if this rules the world in the near future.
The Blue Eyes system is developed because of the need for a real-time monitoring system for a human operator. The approach is innovative since it helps supervise the operator, not the process. The system in its commercial release will avoid threats for humans like weariness, tiredness, over sight and temporal disposition.
It is possible to measure the level of the operator’s conscious brain involvement using eye motility analysis. This requires a CMOS camera integrated into the eye movement sensor, which enables the system to calculate the point of gaze and observe what the operator is actually looking at. This is achieved in the blue eyes technology by MAGIC pointing and almanden eye tracker. There is a voice recognition algorithm which enables the communication between the operator and the central system and simplifies authorization process. Blue Eyes is intended for monitoring and recording the operator’s conscious brain involvement as well as his Physiological conditions. It can sense the feelings of the operator through touch by an emotional mouse.
This paper not only gives an overview of the technology involved but also emphasizes on the hardware requirements like the data acquisition unit (DAU), microcontroller, their working etc. the areas in which the blue eyes technology is being used is illustrated with real time examples.
1. INTRODUCTION:
Is it possible to create a computer which can interact with us as we interact each other? For example imagine in a fine morning you walk on to your computer room and switch on your computer, and then it tells you “Hey friend, good morning you seem to be in a bad mood today. And then it opens your mail box and shows you some of the mails and tries to cheer you. It seems to be a fiction, but it will be the life lead by “BLUE EYES” in the very near future.
Human cognition depends primarily on the ability to perceive, interpret, and integrate audio-visuals and sensoring information. Adding extraordinary perceptual abilities to computers would enable computers to work together with human beings as intimate partners. Researchers are attempting to add more capabilities to computers that will allow them to interact like humans, recognize human presence, talk, listen, or even guess their feelings. This type of project could possibly include gesture recognition, facial recognition, eye tracking, speech recognition, etc.
2. FEATURES:
2.1 EMOTION MOUSE:
A non-invasive way to obtain information about a person is through touch. People use their computers to obtain, store and manipulate data using their computer. In order to start creating smart computers, the computer must start gaining information about the user. Our proposed method for gaining user information through touch is via a computer input device, the mouse. From the physiological data obtained from the user, an emotional state may be determined which would then be related to the task the user is currently doing on the computer. Over a period of time, a user model will be built in order to gain a sense of the user's personality. The scope of the project is to have the computer adapt to the user in order to create a better working environment where the user is more productive.
2.2 MANUAL AND GAZE INPUT CCASCADED (MAGIC) POINTING:
This work explores a new direction in utilizing eye gaze for computer input. It took two engineering efforts to implement the MAGIC pointing techniques. One was to design and implement an eye tracking system and the other was to implement MAGIC pointing techniques at the operating systems level, so that the techniques can work with all software applications beyond “demonstration” software.
2.2.1 THE IBM ALMADEN EYE TRACKER:
Since the goal of this work is to explore MAGIC pointing as a user interface technique, engineers started out by purchasing a commercial eye tracker (ASL Model 5000) after a market survey. In comparison to the system reported in early studies, this system is much more compact and reliable. However, they felt that it was still not robust enough for a variety of people with different eye characteristics, such as pupil brightness and correction glasses. When the light source is placed on-axis with the camera optical axis, the camera is able to detect the light reflected from the interior of the eye, and the image of the pupil appears bright (see Figure 1).
This effect is often seen as the red-eye in flash photographs when the flash is close to the camera lens.
Bright (left) and dark (right) pupil images resulting from on- and off-axis illumination. The glints, or corneal reflections,
from the on- and off-axis light sources can be easily identified as the bright points in the iris.
The Almaden system uses two near infrared (IR) time multiplexed light sources, composed of two sets of IR LED's, which were synchronized with the camera frame rate. One light source is placed very close to the camera's optical axis and is synchronized with the even frames. Odd frames are synchronized with the second light source, positioned off axis. The two light sources are calibrated to provide approximately equivalent whole-scene illumination. Pupil detection is realized by means of subtracting the dark pupil image from the bright pupil image. After thresholding the difference, the largest connected component is identified as the pupil. This technique significantly increases the robustness and reliability of the eye tracking system.
2.3 SPEECH RECOGNITION:
The user speaks to the computer through a microphone, which, in used; a simple system may contain a minimum of three filters. The more the number of filters used, the higher the probability of accurate recognition. Presently, switched capacitor digital filters are used because these can be custom-built in integrated circuit form. These are smaller and cheaper than active filters using operational amplifiers. The filter output is then fed to the ADC to translate the analogue signal into digital word. The ADC samples the filter outputs many times a second. Each sample represents different amplitude of the signal .Evenly spaced vertical lines represent the amplitude of the audio filter output at the instant of sampling. Each value is then converted to a binary number proportional to the amplitude of the sample. A central processor unit (CPU) controls the input circuits that are fed by the ADCS. A large RAM (random access memory) stores all the digital values in a buffer area. This digital information, representing the spoken word, is now accessed by the CPU to process it further. The values of binary input words are subtracted from the corresponding values in the templates. If both the values are same, the difference is zero and there is perfect match. If not, the subtraction produces some difference or error. The smaller the error, the better the match. When the best match occurs, the word is identified and displayed on the screen or used in some other manner.
