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CHAPTER 1 :-
Introduction :-
The AP is an artificial intelligence–based companion that will be
resident in software and chips embedded in the automobile dashboard. The heart of the
system is a conversation planner that holds a profile of you, including details of your
interests and profession.
A microphone picks up your answer and breaks it down into separate words with
speech-recognition software. A camera built into the dashboard also tracks your lip
movements to improve the
This research suggests that we can make predictions about various aspects of driver
performance based on what we glean from the movements of a driver’s eyes and that a
system can eventually be developed to capture this data and use it to alert people when
their driving has become significantly impaired by fatigue.
The natural dialog car system analyzes a driver’s answer and the
contents of the answer together with his voice patterns to determine if he is alert while
driving. The system warns the driver or changes the topic of conversation if the system
determines that the driver is about to fall asleep. The system may also detect whether a
driver is affected by alcohol or drugs.
CHAPTER 2:-
2.1 What is an artificial passenger?
• Natural language e-companion.
• Sleep preventive device in cars to overcome drowsiness.
• Life safety system.
2.2 What does it do?
• Detects alarm conditions through sensors.
• Broadcasts pre-stored voice messages over the speakers.
• Captures images of the driver.
CHAPTER 3 :-
3.1 Field of invention :-
The present invention relates to a system and method for determining three dimensional head pose, eye gaze direction, eye closure amount, blink detection and flexible feature detection on the human face using image analysis from multiple video sources.
Additionally, the invention relates to systems and methods
that makes decisions using passive video analysis of a human head and face.
These methods can be used in areas of application such as human-performance
measurement,operator monitoring and interactive multi-media.
3.2 Background of the invention :-
Early techniques for determining head-pose used devices that were fixed to the head of the subject to be tracked. For example, reflective devices were attached to the subjects head and using a light source to illuminate the reflectors, the reflector locations were determined.
As such reflective devices are more easily tracked than the head itself, the problem of tracking head-pose was simplified greatly.
Virtual-reality headsets are another example of the subject wearing a device for the purpose of head-pose tracking. These devices typically rely on a directional antenna and radio-frequency sources, or directional magnetic
measurement to determine head-pose.
Wearing a device of any sort is clearly a disadvantage, as the
user's competence and acceptance to wearing the device then directly effects the reliability of the system. Devices are generally intrusive and will affect a
user's behaviour, preventing natural motion or operation. Structured light
techniques that project patterns of light onto the face in order to determine head-pose.
The light patterns are structured to facilitate the recovery of 3D
information using simple image processing. However, the technique is prone
to error in conditions of lighting variation and is therefore unsuitable for use
under natural lighting conditions.
3.3 Examples of systems that use this style of technique
Examples of systems that use this style of technique can be seen
in "A Robust Model-Based Approach for 3D Head Tracking in Video Sequences"
by Marius Malciu and Francoise Preteux, and "Robust 3D Head Tracking Under
Partial Occlusion" by Ye Zhang and Chandra Kambhamettu, both from
Conference of Automatic.
CHAPTER 4
4.1 Devices that are used in AP
The main devices that are used in this artificial passenger are:-
1) Eye tracker.
2) Voice recognizer or speech recognizer.
4.2 How does eye tracking work?
Collecting eye movement data requires hardware and software specifically
designed to perform this function. Eye-tracking hardware is either mounted on a user's
head or mounted remotely. Both systems measure the corneal reflection of an infrared
light emitting diode (LED), which illuminates and generates a reflection off the surface of
the eye. This action causes the pupil to appear as a bright disk in contrast to the
surrounding iris and creates a small glint underneath the pupil . It is this glint that head-
mounted and remote systems use for calibration and tracking.
4.2.1 Hardware:
Head-mounted and remote systems:-
The difference between the head-mounted and remote eye systems is
how the eye tracker collects eye movement data. Head-mounted systems , since they are
fixed on a user's head and therefore allow for head movement, use multiple data points to
record eye movement. To differentiate eye movement from head movement, these
systems measure the pupil glint from multiple angles. Since the unit is attached to the
head, a person can move about when operating a car or flying a plane, for example.
For instance, human factors researchers have used head-mounted eye-
tracking systems to study pilots' eye movements as they used cockpit controls and
instruments to land airplanes (Fitts, Jones, and Milton 1950). These findings led to
cockpit redesigns that improved usability and significantly reduced the likelihood of
incidents caused by human error. More recently, head-mounted eye-tracking systems
have been used by technical communicators to study the visual relationship between
personal digital assistant (PDA) screen layout and eye movement.
Remote systems, by contrast, measure the orientation of the eye relative to
a fixed unit such as a camera mounted underneath a computer monitor . Because remote
units do not measure the pupil glint from multiple angles, a person's head must remain
almost motionless during task performance.
Although head restriction may seem like a significant hurdle to overcome,
Jacob and Karn (2003) attribute the popularity of remote systems in usability to their
relatively low cost and high durability compared with head-mounted systems.
Since remote systems are usually fixed to a computer screen, they are
often used for studying onscreen eye motion. For example, cognitive psychologists have
used remote eye-tracking systems to study the relationship between cognitive scanning
styles and search strategies (Crosby and Peterson 1991). Such eye-tracking studies have
been used to develop and test existing visual search cognitive models. More recently,
human-computer interaction (HCI) researchers have used remote systems to study
computer and Web interface usability.
Through recent advances in remote eye-tracking equipment, a range of
head movement can now be accommodated. For instance, eye-tracking hardware
manufacturer Tobii Technology now offers a remote system that uses several smaller
fixed sensors placed in the computer monitor frame so that the glint underneath the pupil
is measured from multiple angles.
This advance will eliminate the need for participants in eye-tracking
studies to remain perfectly still during testing, making it possible for longer studies to be
conducted using remote systems.