[1] Huu Le, Tat-Jun Chin, Anders Eriksson, Thanh-Toan Do, and David Suter. Deterministic approximate methods for maximum consensus robust fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 842--857, March 2021. [ bib | DOI ]
[2] Guobao Xiao, Hanzi Wang, Jiayi Ma, and David Suter. Segmentation by continuous latent semantic analysis for multi-structure model fitting. International Journal of Computer Vision, 2021. [ bib | DOI ]
[3] D W Tan, S Z Gilani, M Boutrus, G A. Alvares, A J.O. Whitehouse, A Mian, D Suter, and M T. Maybery. Facial asymmetry in parents of children on the autism spectrum. Autism Research, 2021. [ bib | DOI ]
[4] Sundaram Muthu, Ruwan Tennakoon, Reza Hoseinnezhad, David Suter, and Alireza Bab-Hadiashar. Motion segmentation of rgb-d sequences: Combining semantic and motion information using statistical inference. IEEE Trans. Image Processing, 29(1):5557--5570, December 2020. [ bib | DOI ]
[5] Diana Tan, Murray Maybery, Syed Zulqarnain Gilani, Gail Alvares, Ajmal Mian, David Suter, and Andrew Whitehouse. A broad autism phenotype expressed in facial morphology. Translational Psychiatry, 10(1), 2020. [ bib | DOI ]
[6] H. Wang, G. Xiao, Y. Yan, and D. Suter. Searching for representative modes on hypergraphs for robust geometric model fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(3):697--711, March 2019. [ bib | DOI ]
[7] Guobao Xiao, Hanzi Wang, Yan Yan, and David Suter. Superpixel-guided two-view deterministic geometric model fitting. International Journal of Computer Vision, May 2018. [ bib | DOI | http ]
[8] T. J. Chin, P. Purkait, A. Eriksson, and D. Suter. Efficient globally optimal consensus maximisation with tree search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4):758--772, April 2017. [ bib | DOI ]
[9] T. Lai, H. Wang, Y. Yan, G. Xiao, and D. Suter. Efficient guided hypothesis generation for multi-structure epipolar geometry estimation. Computer Vision and Image Understanding, 154:152--165, 2017. [ bib | DOI | http ]
[10] P. Purkait, T. J. Chin, A. Sadri, and D. Suter. Clustering with hypergraphs: The case for large hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence, PP(99):1--1, 2017. [ bib | DOI ]
[11] Guobao Xiao, Hanzi Wang, Taotao Lai, and David Suter. Hypergraph modelling for geometric model fitting. Pattern Recognition, 60:748 -- 760, 2016. [ bib | DOI | http ]
[12] R. B. Tennakoon, A. Bab-Hadiashar, Z. Cao, R. Hoseinnezhad, and D. Suter. Robust model fitting using higher than minimal subset sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2):350--362, Feb 2016. [ bib | DOI ]
[13] A. Parra Bustos, T. J. Chin, A. Eriksson, H. Li, and D. Suter. Fast rotation search with stereographic projections for 3d registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11):2227--2240, Nov 2016. [ bib | DOI ]
[14] J. Zaragoza, T. J. Chin, Q. H. Tran, M. S. Brown, and D. Suter. As-projective-as-possible image stitching with moving dlt. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7):1285--1298, July 2014. [ bib | DOI ]
[15] Y. Yan, H. Wang, and D. Suter. Multi-subregion based correlation filter bank for robust face recognition. Pattern Recognition, 47(11):3487--3501, 2014. [ bib | DOI | http ]
[16] Q.H. Tran, T.-J. Chin, W. Chojnacki, and D. Suter. Sampling minimal subsets with large spans for robust estimation. International Journal of Computer Vision, 106(1):93--112, 2014. [ bib | DOI | http ]
[17] T. T. Pham, T. J. Chin, J. Yu, and D. Suter. The random cluster model for robust geometric fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(8):1658--1671, Aug 2014. [ bib | DOI ]
[18] T. T. Pham, T. J. Chin, K. Schindler, and D. Suter. Interacting geometric priors for robust multimodel fitting. IEEE Transactions on Image Processing, 23(10):4601--4610, Oct 2014. [ bib | DOI ]
[19] Jin Yu, Anders Eriksson, Tat-Jun Chin, and David Suter. An adversarial optimization approach to efficient outlier removal. Journal of Mathematical Imaging and Vision, 48(3):451--466, 2014. [ bib | DOI | http ]
[20] T. Sathyan, T. J. Chin, S. Arulampalam, and D. Suter. A multiple hypothesis tracker for multitarget tracking with multiple simultaneous measurements. IEEE Journal of Selected Topics in Signal Processing, 7(3):448--460, June 2013. [ bib | DOI ]
[21] Q.-H. Tran, T.-J. Chin, W. Chojnacki, and D. Suter. Sampling minmal subsets with large spans for robust parameter estimation. International Journal on Computer Vision, 2013. [ bib ]
[22] H.S. Wong, T.-J. Chin, J. Yu, and D. Suter. A simultaneous sample-and-filter strategy for robust multi-structure model fitting. Computer Vision and Image Understanding, 117(12):1755--1769, 2013. [ bib | DOI | http ]
[23] Hoi Sim Wong, Tat-Jun Chin, Jin Yu, and David Suter. Mode seeking over permutations for rapid geometric model fitting. Pattern Recognition, 46(1):257--271, 2013. [ bib | DOI | http ]
[24] Hanzi Wang, Tat-Jun Chin, and David Suter. Simultaneously fitting and segmenting multiple-Structure data with outliers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(6):1177--1192, June 2012. [ bib | DOI | http ]
[25] Tat-Jun. Chin, Jin Yu, and David Suter. Accelerated hypothesis generation for multi-structure data via preference analysis. IEEE Trans. Pattern Analysis and Machine Intelligence, 34(4):625--638, April 2012. [ bib | DOI | http ]
[26] Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, and David Suter. Reply to: Comments on joint detection and estimation of multiple objects from image observations. Signal Processing, IEEE Transactions on, 60(3):1540--1541, March 2012. [ bib | DOI | http ]
[27] Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo, and David Suter. Visual tracking of numerous targets via multi-Bernoulli filtering of image data. Pattern Recognition, 45(10):3625--3635, 2012. [ bib | DOI | http ]
[28] Weiming Hu, Haiqiang Zuo, Ou Wu, Yunfei Chen, Zhongfei Zhang, and David Suter. Recognition of adult images, videos, and web page bags. ACM Trans. Multimedia Comput. Commun. Appl., 7S:28:1--28:24, October 2011. [ bib | DOI | http ]
[29] Tat-Jun Chin, Hanzi Wang, and David Suter. Boosting histograms of descriptor distances for scalable multiclass specific scene recognition. Image and Vision Computing, 29(4):241--250, March 2011. [ bib | DOI | http ]
[30] R. Hoseinnezhad, A. Bab-Hadiashar, and D. Suter. Finite sample bias of robust estimators in segmentation of closely spaced structures: A comparative study. Journal of Mathematical Imaging and Vision, 37(1):66--84, 2010. [ bib | DOI | http ]
[31] Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, and D. Suter. Joint detection and estimation of multiple objects from image observations. IEEE Trans. Signal Processing, 58(10):5129--5141, 2010. [ bib | DOI | http ]
[32] P. Chen and D. Suter. Simultaneously estimating the fundamental matrix and homographies. IEEE Trans. on Robotics, 25(6):1425--1431, December 2009. [ bib | DOI | http ]
[33] Hang Zhou, Liang Wang, and D. Suter. Human action recognition by feature-reduced Gaussian Process Classification. Pattern Recognition Letters, 30(12):1059--1066, September 2009. [ bib | DOI | http ]
[34] P. Chen and D. Suter. Error analysis in homography estimation by first order approximation tools: A general technique. Journal of Mathematical Imaging and Vision, 33(3):281--295, March 2009. [ bib | DOI | http ]
[35] P. Chen and D. Suter. Rank constraints for homographies over two views: Revisiting the rank four constraint. International Journal of Computer Vision, 81(2):205--225, February 2009. [ bib | DOI | http ]
[36] EeHui Lim and D. Suter. 3D terrestrial LIDAR classifications with super-voxels and multi-scale conditional random field. CAD, 41(10):701--710, 2009. [ bib | DOI | http ]
[37] Tat Jun Chin and David Suter. Out-of-sample extrapolation of learned manifolds. IEEE Trans. Pattern Analysis and Machine Intelligence, 30(9):1547--1556, September 2008. [ bib | DOI | http ]
[38] K. Schindler, D. Suter, and H. Wang. A model-selection framework for multibody structure-and-motion of image sequences. Int. Journal of Computer Vision, 79(2):159--177, August 2008. [ bib | DOI | http ]
[39] L. Wang and D. Suter. Visual learning and recognition of sequential data manifolds with applications to human movement analysis. Computer Vision and Image Understanding, 110(2):153--172, May 2008. [ bib | DOI | http ]
[40] K. Schindler and D. Suter. Object detection by global contour shape. Pattern Recognition, 41(12):3736--3748, 2008. [ bib | DOI | http ]
[41] H. Wang, D. Suter, K. Schindler, and C. Shen. Adaptive object tracking based on an effective appearance filter. IEEE Trans. Pattern Analysis and Machine Intelligence, 29(9):1661--1667, September 2007. [ bib | DOI | http ]
[42] P. Chen and D. Suter. A bilinear approach to the parameter estimation of a general heteroscedastic linear system, with application to conic fitting. Journal of Mathematical Imaging and Vision, 28(3):191--208, July 2007. [ bib | DOI | http ]
[43] L. Wang and D. Suter. Learning and matching of dynamic shape manifolds for human action recognition. IEEE Trans. Image Processing, 16(6):1646--1661, June 2007. [ bib | DOI | http ]
[44] Tat-Jun Chin and David Suter. Incremental kernel principal component analysis. IEEE Trans. Image Processing, 16(6):1662--1674, June 2007. [ bib | DOI | http ]
[45] Kenji Yamamoto, Tomohiro Yendo, Toshiaki Fujii, Masayuki Tanimoto, and David Suter. Colour correction for multiple-camera system by using correspondences. The Journal of The Institute of Image Information and Television Engineers, 61(2):213--222, 2007. [ bib | DOI ]
[46] H. Wang and D. Suter. A consensus based method for tracking: Modelling background scenario and foreground appearance. Pattern Recognition, 40(3):1091--1105, 2007. [ bib | DOI | http ]
[47] P. Chen and D. Suter. An analysis of linear subspace approaches for computer vision and pattern recognition. International Journal of Computer Vision, 68(1):83--106, 2006. [ bib | DOI | http ]
[48] K. Schindler and D. Suter. Two-view multibody structure-and-motion with outliers through model selection. IEEE Trans. Pattern Analysis and Machine Intelligence, 28(6):983--995, 2006. [ bib | DOI | http ]
[49] N. Gheissari, A. Bab-Hadiashar, and D. Suter. Parametric model-based motion segmentation using surface selection criterion. Computer Vision and Image Understanding, 102(2):214--226, 2006. [ bib | DOI | http ]
[50] P. Tissainayagam and D. Suter. Object tracking in image sequences using point features. Pattern Recognition, 38(1):105--113, 2005. [ bib | DOI | http ]
[51] P. Chen and D. Suter. Subspace-based face recognition: Outlier detection and a new distance criterion. Int. Journal Pattern Recognition and Artificial Intelligence, 19(4):479--493, 2005. [ bib | DOI | http ]
[52] H. Wang and D. Suter. Robust adaptive-scale parametric model estimation for computer vision. IEEE Trans. Pattern Analysis and Machine Intelligence, 26(11):1459--1479, November 2004. [ bib | DOI | http ]
[53] H. Wang and D. Suter. MDPE: A very robust estimator for model fitting and range image segmentation. Int. J. of Computer Vision, 59(2):139--166, September 2004. [ bib | DOI | http ]
[54] P. Tissainayagam and D. Suter. Assessing the performance of corner detectors for point feature tracking applications. Image and Vision Computing, 22(8):663--679, August 2004. [ bib | DOI | http ]
[55] P. Chen and D. Suter. Recovering the missing components in a large noisy low-rank matrix: Application to SFM. IEEE Trans. Pattern Analysis and Machine Intelligence, 26(8):1051--1063, August 2004. [ bib | DOI | http ]
[56] P. Tissainayagam and D. Suter. Contour tracking with automatic motion model switching. Pattern Recognition, 36(10):2411--2427, October 2003. [ bib | DOI | http ]
[57] H. Wang and D. Suter. Using symmetry in robust model fitting. Pattern Recognition Letters, 24(16):2953--2966, 2003. [ bib | DOI | http ]
[58] P. Tissainayagam and D. Suter. Performance measures for assessing contour trackers. International Journal of Image and Graphics, 2(2):343--359, April 2002. [ bib | DOI | http ]
[59] P. Tissainayagam and D. Suter. Performance prediction analysis of linear point feature trackers based on different motion models. Computer Vision and Image Understanding, 84(1):104--125, October 2001. [ bib | DOI | http ]
[60] P. Tissainayagam and D. Suter. Visual tracking with automatic motion model switching. Pattern Recognition, 34:641--660, 2001. [ bib | DOI | http ]
[61] D. Suter and F. Chen. Left ventricular motion reconstruction based on elastic vector splines. IEEE Trans. Medical Imaging, 19(4):295--305, April 2000. [ bib | DOI | http ]
[62] A. Bab-Hadiashar and D. Suter. Robust segmentation of visual data using ranked unbiased scale estimate. ROBOTICA, International Journal of Information, Education and Research in Robotics and Artificial Intelligence, 17:649--660, 1999. [ bib | DOI | http ]
[63] F. Chen and D. Suter. Div-curl vector quasi-interpolation on a finite domain. Mathematical and Computer Modelling, 30(2):179--204, 1999. [ bib | DOI | http ]
[64] A. Bab-Hadiashar and D. Suter. Robust optic flow computation. International Journal of Computer Vision, 29(1):59--77, August 1998. [ bib | DOI | http ]
[65] F. Chen and D. Suter. Using a fast multipole method to accelerate the evaluation of splines. IEEE Computational Science and Engineering, 5(3):24--31, July-September 1998. [ bib | DOI | http ]
[66] F. Chen and D. Suter. Fast evaluation of vector splines in three dimensions. Journal of Computing, 61(3):189--213, 1998. [ bib | DOI | http ]
[67] D. Suter. Mixed-finite element based motion estimation. Innovation and Technology in Biology and Medicine, 15(3):292--307, 1994. [ bib ]
[68] D. Suter. Fast evaluation of splines using Poisson formula. International Journal of Scientific Computing and Modeling, 1(1):70--87, 1994. [ bib ]
[69] D. Suter. Mixed finite element based neural networks in visual reconstruction. Int. Journal. of Pattern Recognition and Artificial Intelligence, 6(1):113--129, April 1992. [ bib | DOI | http ]
[70] D. Suter. Constraint networks in vision. IEEE Transactions on Computers, 40(12):1359--1367, December 1991. [ bib | DOI | http ]
[71] X. Deng, T. Dillon, K. lew, J. Rankin, E. Smith, and D. Suter. Optimal topologies of transputers for different classes of problems. Comput. Syst. Sci. Eng., 5(1):36--41, January 1990. [ bib | http ]

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