understanding the benefits of gaze-enhanced visual search

12
Pernilla Qvarfordt, Jacob T. Biehl, Gene Golovchinsky and Tony Dunnigan FX Palo Alto Laboratory Palo Alto, California, USA

Upload: fxpal

Post on 10-Jul-2015

872 views

Category:

Technology


2 download

TRANSCRIPT

Page 1: Understanding the Benefits of Gaze-Enhanced Visual Search

Pernilla Qvarfordt, Jacob T.

Biehl, Gene Golovchinsky and

Tony Dunnigan

FX Palo Alto Laboratory

Palo Alto, California, USA

Page 2: Understanding the Benefits of Gaze-Enhanced Visual Search

• Radiologist inspect medical images

• Airport security inspects x-rays of luggage

• Satellite images are inspect for threats

• Quality control of products often include

visual inspection

Page 3: Understanding the Benefits of Gaze-Enhanced Visual Search

• We miss looking everywhere– Radiologist overall error

rate ~20%• (Goddard et al., 2001)

• Current solutions:– Systematic inspection for all

parts of the image

– Documentation of review process

– Second reviewer

– Pattern recognitions models (e.g CAD)

(From Mello-Thoms et al. ETRA 2002)

Page 4: Understanding the Benefits of Gaze-Enhanced Visual Search

• Training– Prescribed scan paths

• Kollera, Drury and Schwaninger (2009), Nickles, Melloy and Gramapadhye (2003)

– Scan paths from expert to guide novices • Sadasvian et al. (2005)

• Improving user interfaces– Augementing display of images

• Haiman et al (2004)

– Segmentation of images• Forlines and Balakrishnan (2009)

– Re-presentation of viewed but not selected regions • Nodine and Kundel (1987)

Page 5: Understanding the Benefits of Gaze-Enhanced Visual Search

Phase 1 Phase 2

Gaze Data

Detect

fixations

Cluster

fixations

Determine

clusters to

exclude

Page 6: Understanding the Benefits of Gaze-Enhanced Visual Search

• 2 x 2 within-subject design & 8 participants

• 24 images: 6 images per condition– 1 training image per condition

• 260-300 shapes– ~25 x 25 pixels

• 5-20 targets per image (random)– 10-40 close distractors

• 67.5 sec per phase– Each segment shown 7.5 sec

• Gaze block: 270 ms threshold to block cluster

• Tobii X120 Eye tracker & 18” CRT Monitor

Gaze blockNo block

Segm

enta

tion

Full im

age

Target Close

distractors

Page 7: Understanding the Benefits of Gaze-Enhanced Visual Search

• Overall no difference in True Positive identifications after both phases

• Increase in True Positive rate in 2nd phase (Block + full image)– Near sig. interaction

• Increase in FN not viewed in 1st

phase transitioning to TP in 2nd

phase (Block + full image)– Sig. interaction

• Significant reduced mental workload (TLX) for Gaze Block

Page 8: Understanding the Benefits of Gaze-Enhanced Visual Search

• Overall no difference in True Positive identifications after both phases

• Increase in True Positive rate in 2nd phase (Block + full image)– Near sig. interaction

• Increase in FN not viewed in 1st

phase transitioning to TP in 2nd

phase (Block + full image)– Sig. interaction

• Significant reduced mental workload (TLX) for Gaze Block

Page 9: Understanding the Benefits of Gaze-Enhanced Visual Search

• Longer durations on True

Positives than on False

Negatives

– Inline with previous research:• (Nodine and Kundel, 1987; Manning,

Ethell and Donovan, 2001)

• Adopt to fixation length

– Longer fixation in phase 2

– Sig. shorter fixation on FN

viewed in phase 1 with gaze

block

550 ms 1032 ms

Page 10: Understanding the Benefits of Gaze-Enhanced Visual Search

• How to use gaze patterns to guide

inspectors to better performance?

– Optimize use of the two phases

• How to combine information from gaze

and image processing to guide inspectors

to important parts of the image?

Page 11: Understanding the Benefits of Gaze-Enhanced Visual Search

• Two phase inspection method

– Reduces workload (with gaze block)

– Have positive effect on FN not viewed

transitioning to TP during

– Possible to estimate targets benefiting from

second review

Page 12: Understanding the Benefits of Gaze-Enhanced Visual Search

Pernilla Qvarfordt, Jacob T.

Biehl, Gene Golovchinsky and

Tony Dunnigan

FX Palo Alto Laboratory

Palo Alto, California, USA