User:JeffPerry/FoveatedImagingDraft

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Foveated imaging is a gaze contingent form of digital image processing in which the image resolution, or amount of detail, varies across the image according to one or more "fixation points" or "regions of interest". The regions of interest may be specified in many ways. For example, one may use a pointing device, like a computer mouse, to specify the high resolution regions of the image. Eye trackers are also commonly used in research settings to specify the region of interest in order to study eye movements. [1] Regions of interest may also be determined automatically using computer algorithms. [2] [3]

Foveated imaging is modeled after the human visual system where the highest resolution region corresponds to the center of the retina, the fovea.

Some common applications of foveated imaging include image compression and visual simulation. [4] [5] [6] For descriptions of these and other applications, see the list below.

Foveated imaging also is commonly referred to as space variant imaging or gaze contingent imaging.

Contents

[edit] Applications

  • Compression

Contrast sensitivity falls off dramatically as one moves from the center of the retina to the periphery. [7] One may take advantage of this fact in order to compactly code images. If one knows the viewer's approximate point of gaze, one may reduce the amount of information contained in the image as the distance from the point of gaze increases. Because the fall-off in image resolution is exponential, the reduction in information can be substantial. Also, foveated imaging may be applied to the image before other types of image compression are applied, and therefore can result in a multiplicative reduction.

Original

Foveated image with fixation point at Stephen F. Austin statue. 16:1 compression.

Foveated image with fixation point on tombstone. 18:1 compression.

Foveated image with fixation point on Texas flag. Only the color channels are foveated in this image, making it hard to distinguish from the original. 3:1 compression.
  • Simulation

Foveated imaging may be used to simulate abitrary visual fields.[8]

  • Foveated Sensors

[9]

  • Image Database Retrieval
  • Quality Assessment

[10]

  • Security

[edit] Examples

Foveated image (luminance channel only)

Foveated image

[edit] References

  1. ^ McConkie G W and Rayner K (1975) The span of the effective stimulus during a fixation in reading, Perception & Psychophysics, 17, 578–86
  2. ^ Z. Wang, L. Lu and A. C. Bovik, "Foveation scalable video coding with automatic fixation selection," IEEE Trans. on Image Processing, Vol: 12 No: 2, February 2003.
  3. ^ R. G. Raj, W. S. Geisler, R. A. Frazor, A. C. Bovik, "Contrast statistics for foveated visual systems: Fixation selection by minimizing contrast entropy" Journal of the Optical Society of America.
  4. ^ J.A. Boluda, F. Pardo, T. Kayser, J.J. P'erez, and J. Pelechano. A new foveated space-variant camera for robotic applications. In IEEE, International Conference on Electronics Circuits And Systems, ICECS'96, Rodos, Greece, October 1996.
  5. ^ Geisler, W.S. and Perry, J.S. (1998) A real-time foveated multi-resolution system for low-bandwidth video communication. In B. Rogowitz and T. Pappas (Eds.), Human Vision and Electronic Imaging, SPIE Proceedings, 3299, 294-305.
  6. ^ Z. Wang and A. C. Bovik, "Embedded foveation image coding," IEEE Transactions on Image Processing, Vol: 10 No: 10, October 2001, Page(s): 1397 -1410
  7. ^ Wandell, Brian A. (1995) Foundations of Vision. ISBN 0-87893-853-2 . p.236
  8. ^ Perry, J.S. and Geisler, W. S. (2002) Gaze-contingent real-time simulation of arbitrary visual fields. In: B. Rogowitz and T. Pappas (Eds.), Human Vision and Electronic Imaging, SPIE Proceedings.
  9. ^ Marc Bolduc, Martin D. Levine. A real-time foveated sensor with overlapping receptive fields. June 1997, Real-Time Imaging, Volume 3 Issue 3
  10. ^ Z. Wang, A. C. Bovik, L. Lu and J. Kouloheris, "Foveated wavelet image quality index," SPIE’s 46th Annual Meeting, Proc. SPIE, Application of digital image processing XXIV, vol. 4472, July-Aug. 2001.

[edit] See Also

[edit] External Links

[edit] TRASH

Compression Foveated imaging may be used in digital image compression.

Image Database Retrieval Progressive Transmission Foveated Imaging can be used in order to dynamically control image retrieval from a database. This is similar to image compression, but is different in that it . satellite imagery, medical imaging, fingerprint matching

Security

Geisler, W.S., Perry, J.S., Najemnik, J. (2006) Visual search: The role of peripheral information measured using gaze-contingent displays. Journal of Vision, 6, 858-873.

S. Lee, C. Podilchuk, V. Krishnan and A.C. Bovik, "Foveation-based error resilience and unequal error protection over mobile networks," Journal of VLSI Signal Processing, Special Issue on Multimedia Communications, Vol: 34 No: 1/2, May 2003.

H. R. Sheikh, B. L. Evans and A. C. Bovik, "Real-Time Foveation Techniques for Low Bit Rate Video Coding," Journal of Real-Time Imaging, Vol: 9 No: 1, February 2003.


S. Lee and A.C. Bovik, "Optimal rate control for real-time, low bitrate foveated video coding," IEEE Transactions on Image Processing, 2001.

(Accepted, August 2005)

http://live.ece.utexas.edu/publications/2006/ta-2006-SPIE.pdf.

Geisler, W.S. and Perry, J.S. (1999) Variable resolution displays for visual communications and simulation. Society for Information Display Technical Digest, 30, 420-423.

Geisler, W. S. and Perry, J.S. (2002) Real-time simulation of arbitrary visual fields. Proceedings of the Eye Tracking Research & Applications Symposium (ACM) 83-87.


Duchowski, Andrew T. and McCormick Bruce H. 1998 "Gaze-Contingent Video Resolution Degradation", in Human Vision and Electronic Imaging II, SPIE, Bellingham, WA.