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Goal: Eye contact detection between two Individuals Single wearable eye tracking device Clinical settings
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Detecting Eye Contact Using Wearable Eye-Tracking Glasses
• Eye contact is important aspect in face to face interaction
In case of children• Atypical pattern of gaze and eye contact • Early sign of autism
Goal:Eye contact detection between two Individuals
Single wearable eye tracking device
Clinical settings
Multiple static camera-distant, problem with frontal view
Mutual eye tracking – Use EOG
Face analysis • Problem of finding and analysing faces
in video • Computer vision • Localize the face and facial parts
(eyebrow, eye, nose, mouth etc)• Gaze estimation using 2D appearance
of eye • Estimate the 3D gaze direction
based on a single image of an eye • Key idea: Learn the appearance model
of the eye for different gaze directions • Large number of samples
OMRON OKAO• Commercial vision library• Detect and analyse child’s face• Takes the video as input • Localizes all facial parts in video
• Estimates 3D head pose • If eyes in the correct position,
• Gaze direction
• Promising result for frontally presented faces
Face analysis result by OKAO
Bounding boxFacial parts Head poseGaze direction
Experimental setup• Objectives
– Record the video and gaze data with minimum obtrusiveness for children
– Allow the analysis of the data for eye contact detection
• Protocol– Interactive session
• 5 to 8 min• Examiner wears the eye tracker glass• Interact with the child• Sitting in front
Provide online annotation by pressing foot pedal----error prone
Experimental setup• During interaction
– Eye gaze was tracked and egocentric video was recorded
• OKAO vision library is applied – Obtain face information of the child
• Location/orientation of face • 3D gaze direction
– Adult gaze information• Provided by eye tracker
Experimental setup• ParticipantsFemale subject of age 16 months Recoded session – 7 min
Method• Combines
– Eye gaze of the examiner– Face information of the child (gaze direction)
• Extract features from gaze and face information
• Train the classifier – Detect existence of eye contact in a specific
frame
Features • Relative location (RL)
– Examiner’s gaze point with respect to child’s eye center
• 3D Gaze direction of the child (GD)– With respect to image plane
• Head orientation (HO)– 3D head position of the child
• Confidence of eye detection (CE)
Method• Detect Eye contact
– Binary classification with ground truth• For each frame in the video and given
feature – Detect the eye contact
• Simple rule works– Fix threshold for RL and GD
• Examiner’s gaze point is close to child’s eye• Child’s gaze facing towards examiner
Gaze direction
Face orientation
Results • Randomly select 60% as training; rest as
testing • 5 trees ---- depth 6
1. RL is more reliable 2. Vertical is more
frequent than horizontal
Performance
OKAO vision library fails to detect correct gaze direction
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