3D Vision
Humans are able to see in the third dimension from a variety of cues, which for most people, is principally driven by information computed from the signals from the two (binocular) eyes. Understanding and modeling the human stereoscopic sense, and using these models for significant applications and visual tasks has been a key focus of LIVE research since the early days of the Computer Vision field. This has included new algorithms and theories for stereoscopic vision as well as 3D-from- 2D images, the first use of color in both human and machine models of stereopsis, applications to microscopy, 3D picture quality and 3D visual discomfort prediction. LIVE has also made fundamental contributions to the theory of 3D natural depth and disparity statistics, and how they may be applied in compelling 3D image processing applications. Some of the key papers follow:
J.R. Jordan and A.C. Bovik, “Computational stereo using color,” Cover Paper of Special Issue on Machine Vision and Image Understanding, IEEE Control Systems Magazine, vol. 8, no. 3, pp. 31-36, June 1988.
C.-C. Chu and A.C. Bovik, “Visible surface reconstruction via local minimax approximation,” Pattern Recognition, vol. 21, no. 4, pp. 303-312, 1988.
N.H. Kim and A.C. Bovik, “A contour-based stereo matching algorithm using disparity continuity,” Pattern Recognition, vol. 21, no. 5, pp. 505-514, 1988.
J.Y. Jou and A.C. Bovik, “Improved initial approximation and intensity-guided discontinuity detection in visible-surface reconstruction,” Computer Vision, Graphics, and Image Processing, vol. 47, pp. 292-326, August 1989.
N.H. Kim, A.C. Bovik and S.J. Aggarwal, “Shape description of biological objects via stereo light microscopy,” IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-20, no. 2, pp. 475-489, March/April 1990.
N.H. Kim, S.J. Aggarwal, A.C. Bovik and K.R. Diller, “3-D model of vascular network in rat skin obtained by stereo vision techniques,” Journal of Microscopy, Special Issue on 3-D Microscopy, vol. 154, no. 4, pp. 275-284, May 1990.
J.R. Jordan, W.S. Geisler and A.C. Bovik, “Color as a source of information in the stereo correspondence process,” Vision Research, vol. 30, no. 12, pp. 1955-1970, December 1990.
J.R. Jordan and A.C. Bovik, “Using chromatic information in edge-based stereo correspondence,” Computer Vision, Graphics, and Image Processing: Image Understanding, vol. 54, no. 1, pp. 98-188, July 1991.
A.C. Bovik, “Three-dimensional microscopy,” Machine Vision and Applications, volume 4, no. 4, pp. 211-213, Fall 1991.
J.R. Jordan and A.C. Bovik, “Using chromatic information in dense stereo correspondence,” Pattern Recognition, vol. 25, no. 4, pp. 367-383, April 1992.
K.A. Bartels, A.C. Bovik, S.J. Aggarwal and K.R. Diller, “The analysis of biological shape changes from multi-dimensional dynamic images,” Journal of Computerized Medical Imaging and Graphics, vol. 17, no. 2, pp. 89-99, May 1993.
B.J. Super and A.C. Bovik, “Shape from texture using local spectral moments,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-17, no. 4, pp. 333- 343, April 1995.
B.J. Super and A.C. Bovik, “Planar surface orientation from texture spatial frequencies,” Pattern Recognition, vol. 28, no. 5, pp. 729-743, May 1995.
C. Yim and A.C. Bovik, “Multiresolution 3-D range segmentation using focus cues,” IEEE Transactions on Image Processing, vol. 7, no. 9, pp. 1283-1299, September 1998.
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.
T.-Y. Chen, A.C. Bovik and L.K. Cormack, “Stereoscopic ranging by matching image modulations,” IEEE Transactions on Image Processing, vol. 8, no. 6, pp. 785-797, June 1999.
S. Gupta, M. Markey and A.C. Bovik, “Advancing the state of the art in 3D human face recognition,” SPIE Newsroom, [Online]. Available: http://spie.org/x14020.xml, May 2007.
Y. Liu, L.K. Cormack and A.C. Bovik, “Disparity statistics in natural scenes,” Journal of Vision, vol. 8, no. 11, art. 19, pp. 1-14, August 2008.
J. Monaco, A.C. Bovik and L.K. Cormack, “Stereoscopic phase differencing: Nonlinearities and multiscale synthesis,” IEEE Transactions on Image Processing, vol. 17, no. 9, pp. 1672- 1684, September 2008.
J. Monaco and A.C. Bovik, “Active, foveated, uncalibrated stereovision,” International Journal of Computer Vision, vol. 85, no. 3, pp. 192-207, December 2009.
T.R. Coffman and A.C. Bovik, “Fast dense stereoscopic ranging via stochastic sampling of match quality,” IEEE Transactions on Image Processing, vol. 19, no. 2, pp. 451-460, February 2010.
S. Gupta, M.K. Markey and A.C. Bovik, “Anthropometric 3D face recognition,” International Journal of Computer Vision, vol. 90, no. 3, pp. 331-349, June 2010.
Y. Liu, L.K. Cormack and A.C. Bovik, “Dichotomy between luminance and disparity features at binocular fixations,” Journal of Vision, vol. 10, no. 12:23, pp. 1-17, December 2010.
Y. Liu, A.C. Bovik and L.K. Cormack, “Statistical modeling of 3D natural scenes with application to Bayesian stereopsis,” IEEE Transactions on Image Processing, vol. 20, no. 9, pp. 2515-2530, September 2011.
X. Cao, A.C. Bovik, Y. Wang and Q. Dai, “Converting 2D video to 3D: An efficient path to a 3D experience,” IEEE Multimedia Magazine, vol. 18, no. 4, pp. 12-17, December 2011.
C.-C. Su, A.C. Bovik and L.K. Cormack, “Color and depth priors in natural images,” IEEE Transactions on Image Processing, vol. 22, no. 6, pp. 2259-2274, June 2013.
M.-J. Chen, L.K. Cormack and A.C. Bovik, “No-reference quality assessment of natural stereopairs,” IEEE Transactions on Image Processing, vol. 22, no. 9, pp. 3379-3391, September 2013.
A.K. Moorthy, C.-C. Su, A. Mittal and A.C. Bovik, “Subjective evaluation of stereoscopic image quality,” Signal Processing: Image Communication, vol. 28, no. 9, pp. 870-883, September 2013.
S. Jahanbin, R. Jahanbin and A.C. Bovik, “Passive three dimensional face recognition using iso-geodesic contours and procrustes analysis,” International Journal of Computer Vision, vol. 105, no. 1, pp. 87-108, doi: 10.1007/s11263-013- 0631-2, October 2013.
M.-J. Chen, C.-C. Su, D.-K. Kwon, L.K. Cormack and A.C. Bovik, “Full-reference quality assessment of stereopairs accounting for rivalry,” Signal Processing: Image Communication, vol. 28, no. 10, pp. 1143-1155, October 2013.
M.-J. Chen, A.C. Bovik and L.K. Cormack, “Study of distortion conspicuity on stereoscopically viewed 3D images,” Journal of the Society for Information Display, vol. 21 no. 11, pp. 491-503, November 2013.
K. Lee, A.K. Moorthy, S. Lee and A.C. Bovik, “3D visual activity assessment based on natural scene statistics,” IEEE Transactions on Image Processing, vol. 23, no. 1, pp. 450- 465, January 2014.
H. Kim, S. Lee and A.C. Bovik, “Saliency measurement on stereoscopic videos,” IEEE Transactions on Image Processing, vol. 23, no. 4, pp. 1476-1490, April 2014.
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.
W. Huang, X. Cao, K. Lu, Q. Dai and A.C. Bovik, “Towards naturalistic 2D-to- 3D conversion,” IEEE Transactions on Image Processing, vol. 24, no. 2, pp. 724-733, February 2015.
J. Park, H. Oh, S. Lee and A.C. Bovik, “3D visual discomfort predictor: Analysis of disparity and neural activity statistics,” IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 1101-1114, March 2015.
C.-C. Su, L.K. Cormack and A.C. Bovik, “Oriented correlation models of distorted natural images with application to natural stereopair quality evaluation,” IEEE Transactions on Image Processing, vol. 24, no. 5, pp. 1685-1699, May 2015.
G.S. Muralidhar, A.C. Bovik and M.K. Markey, “Disparity estimation on stereo mammograms,” IEEE Transactions on Image Processing, vol. 24, no. 9, pp. 2851-2863, September 2015.
T. Kim, S. Lee and A.C. Bovik, “Transfer function model of physiological mechanisms underlying temporal visual comfort experienced when viewing stereoscopic 3D images,” IEEE Transactions on Image Processing, vol 24, no. 11, pp. 4335-4347, November 2015.
H. Oh, S. Lee and A.C. Bovik, “3D visual discomfort prediction: A dynamic accommodation and vergence interaction model,” IEEE Transactions on Image Processing, vol. 25, no. 2, pp. 615-629, February 2016.
K.J. Chen, J. Zhou, J. Sun and A.C. Bovik, “3D visual discomfort prediction using low complexity disparity algorithms,” EURASIP Journal on Image and Video Processing, DOI: 10.1186/s13640-016- 0127-4, vol. 2016, no. 1, pp. 1-10, August 2016.
K.J. Chen and A.C. Bovik, “Visual discomfort prediction on stereoscopic 3D images without explicit disparities,” Signal Processing: Image Communication, vol. 51, pp. 50-60, February 2017.
C.-C. Su, L.K. Cormack and A.C. Bovik, “Bayesian depth estimation from monocular natural images,” Journal of Vision, vol. 17, no. 5, article 22, pp. 1-29, May 2017.