Eye tracking to enhance facial recognition algorithms

EYE TRACKING TO ENHANCE FACIAL RECOGNITION

ALGORITHMSBalu Ramamurthy

Brian LewisDecember 15, 2011

Introduction Facial recognition is growing security

concern

Best recognition algorithm is human brain

Wanted to find a way to use brain information in recognition

If we identify areas humans use to recognize faces, we can get unique results in algorithms

Contents Biometrics Background Eye Tracking Experiment Facial Recognition Experiment Facial Recognition Results Conclusion Future Work

Biometrics Background 2 types of biometrics, identification and

verification

Verification consists of confirming an identity

Identity comes from selecting correct person from a group of candidates

Current algorithms use features extracted from images

Eye Tracking Experiment Used 10 males and 10 females

Ran identification and verification experiments

Females much better at identifying faces

Conducted identification and verification experiments

Verification Experiment 2 Normalized faces shown to participant

Participant asked to say if same person or different person

Identification Experiment Participant looks at image of face for as

long as needed. Then shown 2 by 3 grid of normalized

faces to identify correct face

Eyetracking Heatmap

Facial Recognition Procedure

Each correct image broken up in to 7 by 7 grid

Percentage of fixations for each block extracted.

Facial Recognition Experiment

Experiment 1 gave each block equal distribution

Experiment 2 blocks weighted 0-3 with equal number of blocks in each weight

Experiment 3 blocks given weights of 0-4 based on fixation percentages

Experiment 4 only blocks of 100% fixation were used in algorithms

Facial Recognition Results

Conclusion No significant recognition rate

improvement

Blocks with 100% fixation account for 50% of accuracy

Trial and error in experiments 3 and 4 give hope for future work

Future Work Develop algorithm to properly weight

boxes

Look at using new tasks for eye tracking

Try new facial recognition algorithms on data

Run experiments using specific facial regions