The retina of the human eye has its highest density of photoreceptors for daylight (photopic) vision located at the fovea. This is part of a remarkable resource optimization system whereby the visual system casts its (foveal) gaze at points of visual interest, where it focuses the bulk of its sensing and processing power, while maintaining lower-resolution (parafoveal, perifoveal and peripheral) sensing and processing resources to anticipate future fixations, events, or actions. LIVE has conducted deep research into this key perceptual engineering problem for two decades, including the world’s first, fixating, foveating robotic vision system, popular methods for foveated image and video compression, and foveated computer vision. Some of the key papers follow:
W.N. Klarquist and A.C. Bovik, “FOVEA: A foveated, multi-fixation, vergent active stereo system for dynamic three-dimensional scene recovery,” IEEE Transactions on Robotics and Automation, vol. 14, no. 5, pp. 755-770, October 1998.
S. Lee, M.S. Pattichis and A.C. Bovik, "Foveated video compression with optimal rate control," IEEE Transactions on Image Processing, vol. 10, no. 7, pp. 977-992, July 2001.
Z. Wang and A.C. Bovik, “Embedded foveation image coding,” IEEE Transactions on Image Processing, vol. 10, no. 10, pp. 1397-1410, October 2001.
S. Lee, M.S. Pattichis and A.C. Bovik, "Foveated video quality assessment," IEEE Transactions on Multimedia, vol. 4, no. 1, pp. 129-132, March 2002.
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, pp. 149-166, January 2003.
Z. Wang, L. Lu and A.C. Bovik, “Foveation scalable video coding with automatic fixation selection," IEEE Transactions on Image Processing, vol. 12, no. 2, pp. 243-254, February 2003.
S. Lee and A.C. Bovik, “Fast algorithms for foveated video processing,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 2, pp. 149-162, February 2003.
H.R. Sheikh, B.L. Evans and A.C. Bovik, “Real-time foveation techniques for low bit rate video coding,” Real-Time Imaging, vol. 9, no. 1, pp. 27-40, February 2003.
S. Lee, A.C. Bovik and Y.Y. Kim, “High-quality, low delay foveated visual communications over mobile channels,” Journal of Visual Communication and Image Representation, vol. 16, no. 1, pp. 180-211, January 2005.
R. Raj, W.S. Geisler, R.A. Frazor and A.C. Bovik, “Contrast statistics for foveated vision systems: fixation selection by minimizing contrast entropy,” Journal of the Optical Society of America, vol. 22, no. 10, pp. 2039-2049, October 2005.
S. Liu and A.C. Bovik, “Foveation embedded DCT domain video transcoding,” Journal of Visual Communication and Image Representation, vol. 16, no. 6, pp. 643-667, December 2005. 12. T. Arnow and A.C. Bovik, “Foveated visual search for corners,” IEEE Transactions on Image Processing, vol. 16, no. 3, pp. 813-823, March 2007.
U. Rajashekar, I. van der Linde, A.C. Bovik and L.K. Cormack, “Foveated analysis of image features at fixations,” Vision Research, vol. 47, no. 25, pp. 3160-3172, November 2007.
J. Monaco and A.C. Bovik, “Active, foveated, uncalibrated stereovision,” International Journal of Computer Vision, vol. 85, no. 3, pp. 192-207, December 2009.
J. Park, S. Lee and A.C. Bovik, “3D visual discomfort prediction: Vergence, foveation, and the physiological optics of accomodation,” IEEE Journal on Selected Topics in Signal Processing, vol. 8, no. 3, pp. 415-427, June 2014.