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Ross Micheals Charles Sheppard ASSESSING FACE AND IRIS ACQUISITION.

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Presentation on theme: "Ross Micheals Charles Sheppard ASSESSING FACE AND IRIS ACQUISITION."— Presentation transcript:

1 Ross Micheals Charles Sheppard ASSESSING FACE AND IRIS ACQUISITION

2 Tasks Component of 10-print study One image each of participant face, left iris, right iris Two iris cameras Sensor AParticipant looked straight ahead, minimized amount of proprietary filtering Sensor BParticipant interacted with camera (lined self up with mirror)

3 Context Minimum instructions (demo & basic documentation given to operators) Representative of applications lacking strict control Goal was qualitative assessment of data Effectiveness Efficiency User Satisfaction

4 Effectiveness Goal is to measure image quality Ill-posed problemdepends on application No generally accepted definition (i.e., sample? Metadata? Therefore, we considered a wide variety of factors

5 Face Source: ANSI INCITS Tools Face Alignment Overlay Transformed each factor into … Simple categories (yes, no, N/A) OR Counts OR Standard five-point Lichert Scale

6 Face Alignment Overlay * *Images have been altered for privacy reasons

7 Measurable Qualitative Attributes for Face Images Eye color Hair color Pose Expression Assistance in positioning face Shoulders Background Subject and scene lighting Shadows over the face Shadows in eye-sockets Hot spots Eye glasses Eye patches Radical distortion of the camera lens Horizontally centered face Vertical position of the face Width of head Length of head Facial hairs* Obstruction*

8 Face Statistics Eye ColorCountPercentage Indeterminate3513% Black4718% Blue4918% Brown5019% Dark Brown7327% Dark Green10.40% Gray10.40% Green114% Hair ColorCountPercentage Indeterminate187% Brown6825% Dark Brown8933% Graying Brown104% Graying Dark Brown62% Blond218% Gray Blond41% Black3613% Black with reddish coloring31% Graying Black41% Gray31% Red31% Light Brown20.70% AttributeCountPercentage Eye Glasses6725% Eye Patches00% Facial Hairs8431% Radical distortion of the camera lens 20.75% Obstruction197%

9 Pose GradeCountPercentage % % % % % 1. Not full frontal (wearing head gear, top of head chopped off) 2. Not full frontal (completely chopping off of a shoulder) 3. Not full frontal (head turn at angle) 4. Full frontal (not centered) 5. Full frontal (centered) *Images have been altered for privacy reasons

10 Expression GradeCountPercentage % % % % 2.Eyes looking away from camera and/or squinting 3. A smile were mouth opened and teeth exposedNot full frontal (head turn at angle) 4.A closed jaw smile (no teeth showing) 5. Neutral (non-smiling) with both eyes open and mouth closed *Images have been altered for privacy reasons

11 Shoulders GradeCountPercentage % % % % % 1.Indeterminate squaring (excessive chopping) of shoulder 2.Indeterminate squaring (not enough shoulder shown) 3.Square shoulders (uneven chopping of shoulders) 4.Square shoulders (almost even chopping of shoulders) 5. Square shoulders (even chopping of shoulders) *Images have been altered for privacy reasons

12 Background GradeCountPercentage % % % % 1.Poor segmentation and lack of uniformity (several visible objects in background) 2.Poor segmentation and lack of uniformity (three or four objects in background) 3.Poor segmentation and lack of uniformity (two or three objects in background) 4.Poor segmentation and lack of uniformity (one object in background) *Images have been altered for privacy reasons

13 Subject and Scene Lighting GradeCountPercentage % % % % 1.Lighting not distributed equally on face (excessive shadows caused by head gear) 2.Lighting not distributed equally on face (excessive shadows caused by poor lighting) 3.Lighting not distributed equally on face (fewer shadows) 4.Lighting is distributed almost equally on face *Images have been altered for privacy reasons

14 Shadows over the Face GradeCountPercentage % % % % 51 1.Excessive shadows caused by head gear 2.Large areas of shadows caused by poor lighting 3.Fewer shadow areas caused by better lighting 4.Only in the eye-sockets 5.No shadows *Images have been altered for privacy reasons

15 Shadows in Eye-sockets GradeCountPercentage % % % % % 1.Shadows in both eye- sockets (caused by head gear) 2.Shadows in both eye- sockets (caused by poor sighting) 3.Shadows in only one eye- socket 4.Very little shadow in either eye-socket 5.No shadows in eye-sockets *Images have been altered for privacy reasons

16 Hot Spots GradeCountPercentage % % % % 2.There are multiple areas of hot spots (three or more) 3.There are one or two hot spots 4.Only one softly lighted hot spot 5.No hot spots *Images have been altered for privacy reasons

17 Eye Glasses GradeCountPercentage % % % 3.There is glare from the lenses and shadow casting by the rims 4.There is a small amount of glare 5.No glasses *Images have been altered for privacy reasons

18 Horizontally Centered Face GradeCountPercentage % % % % % 1.Severe chopping of image or excess amount of space on one side 2.There is a larger amount of space on one side than the other 3.There is a small amount of difference in the spacing on one side versus the other 4.There is a very small amount of difference in the spacing on one side versus the other 5.There is perfect centering *Images have been altered for privacy reasons

19 Vertical Position of Face GradeCountPercentage % % % % 2.A large amount of head tilting 3.A small amount of head tilting (eyes are off the horizontal) 4.A very small amount of head tilting (eyes slightly off the horizontal) 5.No head tilting (eyes are perfectly on the horizontal) *Images have been altered for privacy reasons

20 Width of Head GradeCountPercentage % % % % % 1.Part of the head is chopped off 2.The image is chopped too close to the head 3.Part of the person's hair is chopped off 4.The head is turned slightly causing an ear to be out of sight 5.There is adequate head width *Images have been altered for privacy reasons

21 Length of Head GradeCountPercentage % % % % 1.There is head gear or the chopping off of the top the head 2.The image is chopped very close to the top of the head 3.There are sunglasses on top of the head or part of the hair on top of head is chopped off 5.There is adequate head length *Images have been altered for privacy reasons

22 Obstruction GradeCountPercentage % % % % 1.Some form of head gear (hat, cap,….) 2.Sun glasses on top of head or head band 3.Eye glasses on top of head 5.There are no obstructions *Images have been altered for privacy reasons

23 Iris Source: ANSI INCITS Tools Iris Overlay Transformed each factor into … Simple categories (yes, no, N/A) OR Counts OR Standard five-point Lichert Scale

24 Iris Overlay Example

25 Measurable Qualitative Attributes for Iris Images Location of reflections Glasses Focus Visible Iris Image scale Noise Image Orientation Camera type

26 Iris Statistics Attribute Camera Type Scanner AScanner B CountPercentageCountPercentage Participants % % Face image with no iris image32.42%31.94% No face or iris images00%31.94% No left iris images32.42%74.52% No right iris images10.81%42.58%

27 More Iris Statistics Attribute Camera Type Scanner AScanner B Left EyeRight EyeLeft EyeRight Eye CountPercentageCountPercentageCountPercentageCountPercentage Glasses Visible % % % % Raw Images Final Images118100% %142100% % Extended Images Pupil-Only reflections (final images) % % % % Focus on glasses (final images)97.63%86.67% % % Raw images with visible iris Final images with visible iris118100% %142100% %

28 More Iris Statistics Operator tells participant to reposition Scanner YesNo CountPercentageCountPercentage A % % B % % Participant asks about glasses Scanner YesNo CountPercentageCountPercentage A % % B % %

29 Segue Before moving on, consider the following. When does ? Answer is, when we talk about… Efficiency!

30 Efficiency Deceptively ill-posed Example: How long does a photo take? Average camera shutter speed is.001 second Implies we can take photos of 1,000 people in 1 second Despite this obviously flawed leap in logic, we continue to make this mistake

31 Efficiency 10-Print Working Group RFIIntended requirement is five seconds from placement of hand to capture Therefore, must a sequence happen in under 15 seconds? (i.e., ) Just as on the fingerprint side, our approach was to timestamp at a variety eventsallows more flexible reporting However, there is a compromise between what you would like to measure for each participant, and what you can measure

32 Sit Down Picture Taken Done with Picture Picture Process Iris Scanning Process Moves to Iris Scanner Finished Time Start of Iris Scan Finish with Eye 1 (Scanner B Only) Start of Eye 2 (Scanner B Only) Picture and Iris Scan Process

33 Scanner-A Timing Average 0:34 Median 0:27

34 Scanner-A Timing Average 1:14 Median 1:03

35 Scanner-B Timing Average 0:44 Median 0:29

36 Scanner-B Timing Average 1:25 Median 1:11

37 Face Picture Timing Average 0:15 Median 0:13

38 Large-scale Biometric System Data

39 User-satisfaction


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