Topic4-Realtime Drowsiness Detection System Final

8/13/2019 Topic4-Realtime Drowsiness Detection System Final

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Salvatore Vitabile, Alessandra De Paola, Filippo SorbelloDepartment of Biopathology and Medical Biotechnology andForensics, University of Palermo, Italy

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Journal of Ambient Intelligence and Humanized ComputingPublished on March 30, 2011

Chien-Chih(Paul) ChaoChih-Chiang(Michael) Chang

Instructor: Dr. Ann Gordon-Ross


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An embedded monitoring system to detectsymptoms of drivers drowsiness.

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MotivationRelated worksDrowsiness Monitoring System

Eye Regions SegmentationCandidate Eye Regions SelectionDrivers Eyes Detection

Drowsiness Level ComputationExperimental trialsConclusionLimitations & Future Work

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10-20% of all European traffic accidents are dueto the diminished level of attention caused by

fatigue.In the trucking industry about 60% of vehicularaccidents are related to driver hypo-vigilance. [1]Automotive has gained several benefit from theAmbient Intelligent researches involving thedevelopment of sensors and hardware devices

4 / 20[1] Awake Consortium (IST 2000-28062), System for effective assessment of

driver vigilance and warning according to traffic risk estimation (AWAKE),Sep 2001 2004 [Online], available: http://www.awake-eu.org


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The technique categories for preventing driversdrowsiness [2]

Readiness-to-perform and fitness-for-duty

technologiesMathematical models of dynamics alertnessVehicle-based performance technologies

The lateral position Steering wheel movements time-to-line crossingReal-time technologies for monitoring drivers status

Intrusive monitoring systems Non-intrusive monitoring systems

5 / 20[2] Hartley L, Horberry T, Mabbott N, Krueger G (2000) Review of fatigue detection and

prediction technologies. National Road Transport Commission report 642(54469)


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The most accurate techniques are based onphysiological measures

Brain wavesHeart ratePulse rate

Causing annoyance due to require electrodesto be attached to the drivers

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A non-intrusive, real-time drowsinessdetection system.Using FPGA instead of ASIC of DSP

Re-programmabilityPerformanceCosts

IR cameraLow light conditionsBright pupilphenomenon to detect the eyes

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PERCLOS (Percentage of Eye Closure)The driver eyes are closed more than 80%

within a specified time interval is defined asdrowsiness. [3]

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[3] W. W. Wierwille: Historical perspective on slow eyelid closure: Whence PERCLOS?,In Technical Proceedings Ocular Measures of Driver Alertness Conference, FederalHighway Admin., Office Motor Carrier Highway Safety, R. J. Carroll Ed. Washington,D.C., FHWA Tech. Rep. No. MC-99-136, 1999


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Bright Pupil

Threshold Operation

Clipping & MorphologicalOperation


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A list of blobsPossible Eye Pairs

Square Bounding BoxR = a

Quasi-circular shape:

R

a


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Frame 1

[ (X1, Y1) ,(X2, Y2) ]t = 4

Class 1

Coordinate

At t

Class

Frame 2

[ (X1, Y1) ,(X2, Y2) ]t = 3

Class 1

Frame 3

[ (X1, Y1) ,(X2, Y2) ]t = 2

Class 1

Frame 4

[ (X1, Y1) ,(X2, Y2) ]t = 1

Class 1

Class 1

Weight 4

Class 2 Class 3 Class 4 Class 5

0 0 0 0

[ (X1, Y1) ,(X2, Y2) ]t = 5

Class 2

3 1


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JSP DF-402 infrared-sensitive cameraColor camera in daytime

Infrared camera under low light cond.

14 / 20http://www.es.ele.tue.nl/education/oo2/fpga/board.php
http://www2.bren.ucsb.edu/~dturney/WebResources_13/RemoteSensing/RemoteSensing.htmhttp://www2.bren.ucsb.edu/~dturney/WebResources_13/RemoteSensing/RemoteSensing.htm


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Celoxica RC203EXilinX XC2V3000-4 Virtex II FPGA

Handel-C PixelStreams Library

http://www.es.ele.tue.nl/education/oo2/fpga/board.php 15 / 20


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In light controlled environmentDrive-Camera relative distance

Not affected by driver-camera relative distance16 / 20

ID =1


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Vertical and Horizontal of head movement

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ID =2


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Real operation condition(External illumination not controlled)

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ID =3


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An algorithm to detect and track the driverseyes has been developed by exploiting brightpupils phenomenonGood performance on rapid movements ofdrivers head. Performance not affected by driver-camera

relative distance.The drowsiness monitoring system can beused with low light conditions by usinginfrared camera

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Faulty operationsthe driver is wearing glasses

the drivers IR-reflecting objects such as earringDrowsiness usually happen during theevening/night hours

Light poles might be recognized as eyecandidates due to the shape and size on screen

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Documents

Topic4-Realtime Drowsiness Detection System Final