Bibliography - Computer Vision for Visual Effects - page 388

Fields with smoothness-based priors. IEEE Transactions onPatternAnalysis andMachine
Intelligence , 30(6):1068-80, June 2008.
[486] H. Tao, H. Sawhney, and R. Kumar. A global matching framework for stereo computation.
In IEEE International Conference on Computer Vision (ICCV) , 2001.
[487] D. Tell and S. Carlsson. Wide baseline point matching using affine invariants computed
from intensity profiles. In European Conference on Computer Vision (ECCV) , 2000.
[488] J.-P. Thirion. Image matching as a diffusion process: an analogy with Maxwell's demons.
Medical Image Analysis , 2(3):243-60, Sept. 1998.
[489] S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics . MIT Press, 2005.
[490] E. Tola, V. Lepetit, and P. Fua. DAISY: An efficient dense descriptor applied to
wide-baseline stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence ,
32(5):815-30, May 2010.
[491] D. Tolani, A. Goswami, and N. I. Badler. Real-time inverse kinematics techniques for
anthropomorphic limbs. Graphical Models , 62(5):353-88, Sept. 2000.
[492] C. Tomasi and T. Kanade. Detection and tracking of point features. Technical Report
CMU-CS-91-132, Carnegie Mellon University, 1991.
[493] C. Tomasi and T. Kanade. Shape and motion from image streams under orthogra-
phy: a factorization method. International Journal of Computer Vision , 9(2):137-54,
Nov. 1992.
[494] T. Tommasini, A. Fusiello, E. Trucco, andV. Roberto.Making good features trackbetter. In
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) ,
1998.
[495] P. H. Torr, A. W. Fitzgibbon, and A. Zisserman. The problem of degeneracy in struc-
ture and motion recovery from uncalibrated image sequences. International Journal of
Computer Vision , 32(1):27-44, Aug. 1999.
[496] L. Torresani, A. Hertzmann, andC. Bregler. Learning non-rigid 3Dshape from2Dmotion.
In Conference on Neural Information Processing Systems , 2004.
[497] M. Trajkovic and M. Hedley. Fast corner detection. Image and Vision Computing ,
16(2):75-87, 1998.
[498] B. Triggs. Factorization methods for projective structure and motion. In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR) , 1996.
[499] B. Triggs. Autocalibration and the absolute quadric. In IEEE Computer Society Conference
on Computer Vision and Pattern Recognition (CVPR) , 1997.
[500] B. Triggs, P. McLauchlan, R. Hartley, and A. Fitzgibbon. Bundle adjustment — a modern
synthesis. In B. Triggs, A. Zisserman, and R. Szeliski, editors, Vision Algorithms: Theory
and Practice , pages 153-77. Springer, 2000.
[501] G. Turk and M. Levoy. Zippered polygon meshes from range images. In ACM SIGGRAPH
(ACM Transactions on Graphics) , 1994.
[502] G. Turk and J. F. O'Brien. Shape transformation using variational implicit functions. In
ACM SIGGRAPH (ACM Transactions on Graphics) , 1999.
[503] T. Tuytelaars and L. Van Gool. Matching widely separated views based on affine invariant
regions. International Journal of Computer Vision , 59(1):61-85, Aug. 2004.
[504] S. Umeyama. Least-squares estimation of transformation parameters between two point
patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence , 13(4):376-80,
Apr. 1991.
[505] R. Unnikrishnan and M. Hebert. Extracting scale and illuminant invariant regions
through color. In British Machine Vision Conference (BMVC) , 2006.
[506] S. Uras, F. Girosi, A. Verri, and V. Torre. A computational approach tomotion perception.
Biological Cybernetics , 60(2):79-87, Dec. 1988.
[507] R. Urtasun, D. Fleet, and P. Fua. 3D people tracking with Gaussian process dynam-
ical models. In IEEE Computer Society Conference on Computer Vision and Pattern
Recognition (CVPR) , 2006.
[508] K. vande Sande, T. Gevers, andC. Snoek. Evaluating color descriptors for object and scene
recognition. IEEE Transactions on Pattern Analysis andMachine Intelligence , 32(9):1582-
96, Sept. 2010.