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ABSTRACT

A new experiment is presented that demonstrates the usefulness of an image space modulation technique called subtle gaze direction (SGD) for guiding the user in a simple searching task. SGD uses image space modulations in the luminance channel to guide a viewer's gaze about a scene without interrupting their visual experience. The goal of SGD is to direct a viewer's gaze to certain regions of a scene without introducing noticeable changes in the image. Using a simple searching task, we compared performance using no modulation, using subtle modulation, and using obvious modulation. Results from the experiments show improved performance when using subtle gaze direction, without affecting the user's perception of the image. We then extend the experiment to evaluate performance with the presence of distractors. The distractors took the form of extra modulations, which do not correspond to a target in the image. Experimentation shows, that, even in the presence of distractors, more accurate results are returned on a simple search task using SGD, as compared to results returned when no modulation at all is used. Results establish the potential of the method for a wide range of applications including gaming, perceptually based rendering, navigation in virtual environments, and medical search tasks.

REFERENCES

• 1: Reynold Bailey , Ann McNamara , Nisha Sudarsanam , Cindy Grimm, Subtle gaze direction, ACM Transactions on Graphics (TOG), v.28 n.4, p.1-14, August 2009 [doi>10.1145/1559755.1559757]
• 2: Bilska-Wolak, A., Floyd, C., Nolte, L., and Lo, J. 2003. Application of likelihood ratio to classification of mammographic masses; performance comparison to case-based reasoning. Med. Phys. 30, 949--958.
• 3: Boot, W. R., Neider, M. B., and Kramer, A. F. 2009. Training and transfer of training in the search for camouflaged targets. Attention Percept. Psychophys. 71, 4, 950--963.
• 4: Kirsten Cater , Alan Chalmers , Patrick Ledda, Selective quality rendering by exploiting human inattentional blindness: looking but not seeing, Proceedings of the ACM symposium on Virtual reality software and technology, November 11-13, 2002, Hong Kong, China [doi>10.1145/585740.585744]
• 5: Doug DeCarlo , Anthony Santella, Stylization and abstraction of photographs, Proceedings of the 29th annual conference on Computer graphics and interactive techniques, July 23-26, 2002, San Antonio, Texas [doi>10.1145/566570.566650]
• 6: Duchowski, A. T. 2002. A breadth-first survey of eye tracking applications. Behav. Res. Methods 34, 4, 455--470.
• 7: Ayman El-Baz , Aly Farag , Georgy Gimel'farb , Robert Falk , Mohamed A. El-Ghar , Tarek Eldiasty, A Framework for Automatic Segmentation of Lung Nodules from Low Dose Chest CT Scans, Proceedings of the 18th International Conference on Pattern Recognition, p.611-614, August 20-24, 2006 [doi>10.1109/ICPR.2006.66]
• 8: Youngmin Kim , Amitabh Varshney, Saliency-guided Enhancement for Volume Visualization, IEEE Transactions on Visualization and Computer Graphics, v.12 n.5, p.925-932, September 2006 [doi>10.1109/TVCG.2006.174]
• 9: Robert Kosara , Silvia Miksch , Helwig Hauser, Semantic Depth of Field, Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01), p.97, October 22-23, 2001
• 10: Greg Ward Larson , Rob Shakespeare, Rendering With Radiance: The Art And Science Of Lighting Visualization, Booksurge Llc, 2004
• 11: David Luebke , Benjamin Watson , Jonathan D. Cohen , Martin Reddy , Amitabh Varshney, Level of Detail for 3D Graphics, Elsevier Science Inc., New York, NY, 2002
• 12: Mack, A. and Rock, I. 1998. Inattentional Blindness. MIT Press, Cambridge, MA.
• 13: Matei Mancas , Bernard Gosselin , Benoit Macq, Automatic Fast Detection of Tumor Suspect Areas on CT Scan, Proceedings of the conference on Visualization '04, p.598.33, October 10-15, 2004 [doi>10.1109/VIS.2004.9]
• 14: Mitchell, G. E. 2004. Taking control over depth of field: Using the lens blur filter in Adobe Photoshop CS. The Light's Right Studio. http://www.outbackphoto.com/workflow/wf_51/essay.html
• 15: Neider, M. B. and Zelinsky, G. J. 2006. Searching for camouflaged targets: Effects of target-background similarity on visual search. Vision Res. 46, 14, 2217--2235.
• 16: Ogden, T. E. and Miller, R. F. 1966. Studies of the optic nerve of the rhesus monkey: Nerve fiber spectrum and physiological properties. Vision Res. 6, 485--506.
• 17: O'Sullivan, C., Dingliana, J., and Howlett, S. 2003. Eye-movements and interactive graphics. http://isg.cs.tcd.ie/osulliv/Pubs/finalgaze.pdf.
• 18: Rayner, K. 1975. The perceptual span and peripheral cues in reading. Cognitive Psych. 7, 65--81.
• 19: Schwaninger, A., Hardmeier, D., and Hofer, F. 2004. Measuring visual abilities and visual knowledge of aviation security screeners. In Proceedings of the Carnahan Conference on Security Technology (ICCST'04). IEEE, Los Alamitos, CA, 258--264.
• 20: Adrian Schwaninger , Stefan Michel , Anton Bolfing, A statistical approach for image difficulty estimation in x-ray screening using image measurements, Proceedings of the 4th symposium on Applied perception in graphics and visualization, July 25-27, 2007, Tubingen, Germany [doi>10.1145/1272582.1272606]
• 21: Simons, D. and Chabris, C. 1995. Gorillas in our midst: Sustained inattentional blindness for dynamic events. Br. J. Dev. Psych. 13, 113--142.
• 22: Spillmann, L. 1990. Visual Perception: The Neurophysiological Foundations. Academic Press, San Diego, CA.
• 23: Tourassi, G., Vargas-Voracek, R., Catarious, D., and Floyd, C. 2003. Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information. Med. Phys. 30, 2123--2130.
• 24: Zhuowen Tu , Xiang Sean Zhou , Luca Bogoni , Adrian Barbu , Dorin Comaniciu, Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment, Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p.1544-1551, June 17-22, 2006 [doi>10.1109/CVPR.2006.228]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.3 Picture/Image Generation

Keywords:
Eye tracking, gaze direction, image manipulation, luminance, psychophysics