Professor David Suter

Senior Lecturer

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

My Research
Career
Publications
Grants and Funding
Teaching
Supervision
Contact

I work in Computer Vision (aka Machine Vision, Robotic Vision), Machine Learning, Image Processing and related areas (touches on computer graphics, spatial information etc.).

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Appointments

Date	Position	Institution name
2009 - 2013	Head of School	The University of Adelaide
2008	Professor	The University of Adelaide
2008 - 2010	College of Experts	Australian Research Council
2006 - 2008	Professor	Monash University
2005 - 2005	Associate Dean Research	Monash University
2002 - 2006	Associate Professor	Monash University
1992 - 2001	Senior Lecturer	Monash University
1988 - 1992	Lecturer	La Trobe University

Date	Institution name	Country	Title
1986 - 1990	La Trobe University	Australia	PhD
1985 - 1985	La Trobe University	Australia	MSc (prelim)
1983 - 1984	RMIT	Australia	Grad Dip Computing
1978 - 1978	The Flinders Uni of SA	Australia	Dip Ed
1975 - 1978	The Flinders Uni of SA	Australia	BSc

Journals

Year	Citation
2019	Xiao, G., Wang, H., Yan, Y., & Suter, D. (2019). Superpixel-Guided Two-View Deterministic Geometric Model Fitting. International Journal of Computer Vision, 127(4), 323-339. DOI
2019	Wang, H., Xiao, G., Yan, Y., & Suter, D. (2019). Searching for representative modes on hypergraphs for robust geometric model fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(3), 697-711. DOI Scopus3 WoS1
2017	Chin, T., Purkait, P., Eriksson, A., & Suter, D. (2017). Efficient globally optimal consensus maximisation with tree search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), 758-772. DOI Scopus5 WoS2
2017	Lai, T., Wang, H., Yan, Y., Xiao, G., & Suter, D. (2017). Efficient guided hypothesis generation for multi-structure epipolar geometry estimation. Computer Vision and Image Understanding, 154, 152-165. DOI Scopus3 WoS3
2017	Purkait, P., Chin, T., Sadri, A., & Suter, D. (2017). Clustering with Hypergraphs: The Case for Large Hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(9), 1697-1711. DOI Scopus5 WoS3
2016	Parra Bustos, A., Chin, T., Eriksson, A., Li, H., & Suter, D. (2016). Fast rotation search with stereographic projections for 3D registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), 2227-2240. DOI Scopus8 WoS7
2016	Tennakoon, R., Bab-Hadiashar, A., Cao, Z., Hoseinnezhad, R., & Suter, D. (2016). Robust model fitting using higher than minimal subset sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), 350-362. DOI Scopus14 WoS11 Europe PMC1
2016	Xiao, G., Wang, H., Lai, T., & Suter, D. (2016). Hypergraph modelling for geometric model fitting. Pattern Recognition, 60, 748-760. DOI Scopus11 WoS9
2014	Pham, T., Chin, T., Schindler, K., & Suter, D. (2014). Interacting geometric priors for robust multimodel fitting. IEEE Transactions on Image Processing, 23(10), 4601-4610. DOI Scopus23 WoS17 Europe PMC2
2014	Quoc, H., Chin, T., Chojnacki, W., & Suter, D. (2014). Sampling minimal subsets with large spans for robust estimation. International Journal of Computer Vision, 106(1), 93-112. DOI Scopus12 WoS9
2014	Yu, J., Eriksson, A., Chin, T., & Suter, D. (2014). An adversarial optimization approach to efficient outlier removal. Journal of Mathematical Imaging and Vision, 48(3), 451-466. DOI Scopus2 WoS2
2014	Zaragoza, J., Chin, T., Tran, Q., Brown, M., & Suter, D. (2014). As-projective-as-possible image stitching with moving DLT. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7), 1285-1298. DOI Scopus92 WoS66
2014	Yan, Y., Wang, H., & Suter, D. (2014). Multi-subregion based correlation filter bank for robust face recognition. Pattern Recognition, 47(11), 3487-3501. DOI Scopus18 WoS13
2014	Pham, T., Chin, T., Yu, J., & Suter, D. (2014). The random cluster model for robust geometric fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(8), 1658-1671. DOI Scopus45 WoS34 Europe PMC2
2013	Wong, H., Chin, T. J., Yu, J., & Suter, D. (2013). Mode seeking over permutations for rapid geometric model fitting. Pattern Recognition, 46(1), 257-271. DOI Scopus9 WoS8
2013	Wong, H., Chin, T. J., Yu, J., & Suter, D. (2013). A simultaneous sample-and-filter strategy for robust multi-structure model fitting. Computer Vision and Image Understanding, 117(12), 1755-1769. DOI Scopus9 WoS9
2013	Sathyan, T., Chin, T. J., Arulampalam, S., & Suter, D. (2013). A multiple hypothesis tracker for multitarget tracking with multiple simultaneous measurements. IEEE Journal on Selected Topics in Signal Processing, 7(3), 448-460. DOI Scopus56 WoS38
2012	Hoseinnezhad, R., Vo, B., Vo, B., & Suter, D. (2012). Visual tracking of numerous targets via multi-Bernoulli filtering of image data. Pattern Recognition, 45(10), 3625-3635. DOI Scopus110 WoS100
2012	Wang, H., Chin, T., & Suter, D. (2012). Simultaneously fitting and segmenting multiple-structure data with outliers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(6), 1177-1192. DOI Scopus69 WoS61 Europe PMC4
2012	Vo, B. N., Vo, B. T., Pham, N., & Suter, D. (2012). Reply to "Comments on 'Joint detection and estimation of multiple objects from image observations'". IEEE Transactions on Signal Processing, 60(3), 1540-1541. DOI Scopus1
2012	Chin, T., Yu, J., & Suter, D. (2012). Accelerated hypothesis generation for multistructure data via preference analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(4), 625-638. DOI Scopus70 WoS58 Europe PMC9
2011	Hu, W., Zuo, H., Wu, O., Chen, Y., Zhang, Z., & Suter, D. (2011). Recognition of adult images, videos, and web page bags. ACM Transactions on Multimedia Computing Communications and Applications, 7(1 Sp Iss), 28:1-28:24. DOI Scopus12 WoS4
2011	Chin, T. J., Suter, D., & Wang, H. (2011). Boosting histograms of descriptor distances for scalable multiclass specific scene recognition. Image and Vision Computing, 29(4), 241-250. DOI Scopus6 WoS5
2010	Hoseinnezhad, R., Bab-Hadiashar, A., & Suter, D. (2010). 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. DOI Scopus18 WoS17
2010	Vo, B. N., Vo, B. T., Pham, N., & Suter, D. (2010). Joint detection and estimation of multiple objects from image observations. IEEE Transactions on Signal Processing, 58(10), 5129-5141. DOI Scopus223 WoS174
2009	Chen, P., & Suter, D. (2009). Simultaneously estimating the fundamental matrix and homographies. IEEE Transactions on Robotics, 25(6), 1425-1431. DOI Scopus3 WoS1
2009	Chen, P., & Suter, D. (2009). Rank Constraints for Homographies over Two Views: Revisiting the Rank Four Constraint. International Journal of Computer Vision, 81(2), 205-225. DOI Scopus12 WoS10
2009	Chen, P., & Suter, D. (2009). Error Analysis in Homography Estimation by First Order Approximation Tools: A General Technique. Journal of Mathematical Imaging and Vision, 33(3), 281-295. DOI Scopus10 WoS5
2009	Zhou, H., Wang, L., & Suter, D. (2009). Human action recognition by feature-reduced Gaussian process classification. Pattern Recognition Letters, 30(12), 1059-1066. DOI Scopus21 WoS13
2009	Lim, E., & Suter, D. (2009). 3D terrestrial LIDAR classifications with super-voxels and multi-scale Conditional Random Fields. Computer-aided Design, 41(10 Sp Iss), 701-710. DOI Scopus95 WoS70
2008	Chin, T., & Suter, D. (2008). Out-of-sample extrapolation of learned manifolds. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(9), 1547-1556. DOI Scopus28 WoS19 Europe PMC1
2008	Wang, L., & Suter, D. (2008). Visual learning and recognition of sequential data manifolds with applications to human movement analysis. Computer Vision and Image Understanding, 110(2), 153-172. DOI Scopus49 WoS37
2008	Schindler, K., & Suter, D. (2008). Object detection by global contour shape. Pattern Recognition, 41(12), 3736-3748. DOI Scopus40 WoS32
2008	Schindler, K., Suter, D., & Wang, H. (2008). A Model-selection Framework for Multibody Structure-and-Motion of Image Sequences. International Journal of Computer Vision, 79(2), 159-177. DOI Scopus30 WoS25
2007	Wang, H., Suter, D., Schindler, K., & Shen, C. (2007). Adaptive object tracking based on an effective appearance filter. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9), 1661-1667. DOI Scopus166 WoS115 Europe PMC14
2007	Wang, H., & Suter, D. (2007). A consensus-based method for tracking: Modelling background scenario and foreground appearance. Pattern Recognition, 40(3), 1091-1105. DOI Scopus109 WoS70
2007	Chin, T., & Suter, D. (2007). Incremental kernel principal component analysis. IEEE Transactions on Image Processing, 16(6), 1662-1674. DOI Scopus110 WoS77 Europe PMC17
2007	Yamamoto, K., Yendo, T., Fujii, T., Tanimoto, M., & Suter, D. (2007). Colour correction for multiple-camera system by using correspondences. Institute of Image Information and Television Engineers, 61(2), 213-222. DOI Scopus22
2007	Chen, P., & Suter, D. (2007). 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. DOI Scopus7 WoS6
2007	Wang, L., & Suter, D. (2007). Learning and matching of dynamic shape manifolds for human action recognition. IEEE Transactions on Image Processing, 16(6), 1646-1661. DOI Scopus129 WoS90 Europe PMC6
2006	Chen, P., & Suter, D. (2006). An analysis of linear subspace approaches for computer vision and pattern recognition. International Journal of Computer Vision, 68(1), 83-106. DOI Scopus10 WoS5
2006	Schindler, K., & Suter, D. (2006). Two-view multibody structure-and-motion with outliers through model selection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6), 983-995. DOI Scopus56 WoS42 Europe PMC4
2006	Gheissan, N., Bab-Hadiashar, A., & Suter, D. (2006). Parametric model-based motion segmentation using surface selection criterion. Computer Vision and Image Understanding, 102(2), 214-226. DOI Scopus8 WoS7
2005	Tissainayagam, P., & Suter, D. (2005). Object tracking in image sequences using point features. Pattern Recognition, 38(1), 105-113. DOI Scopus75 WoS43
2005	Chen, P., & Suter, D. (2005). Subspace-based face recognition: Outlier detection and a new distance criterion. International Journal of Pattern Recognition and Artificial Intelligence, 19(4), 479-493. DOI Scopus2 WoS1
2004	Tissainayagam, P., & Suter, D. (2004). Assessing the performance of corner detectors for point feature tracking applications. Image and Vision Computing, 22(8), 663-679. DOI Scopus105 WoS69
2004	Chen, P., & Suter, D. (2004). Recovering the missing components in a large noisy low-rank matrix: Application to SFM.. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8), 1051-1063. DOI Scopus86 WoS73 Europe PMC11
2004	Suter, D., Comaniciu, D., & Kanatani, K. (2004). Special issue on statistical methods in video processing. Image and Vision Computing, 22(2), 83-84. DOI
2004	Wang, H., & Suter, D. (2004). MDPE: A very robust estimator for model fitting and range image segmentation. International Journal of Computer Vision, 59(2), 139-166. DOI Scopus53 WoS35
2004	Wang, H., & Suter, D. (2004). Robust adaptive-scale parametric model estimation for computer vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(11), 1459-1474. DOI Scopus108 WoS93 Europe PMC9
2004	Comaniciu, D., Kanatani, K., Mester, R., & Suter, D. (2004). Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3247.
2003	Wang, H., & Suter, D. (2003). Using symmetry in robust model fitting. Pattern Recognition Letters, 24(16), 2953-2966. DOI Scopus12 WoS12
2003	Tissainayagam, P., & Suter, D. (2003). Contour tracking with automatic motion model switching. Pattern Recognition, 36(10), 2411-2427. DOI Scopus14 WoS11
2002	Bab-Hadiashar, A., Gheissari, N., & Suter, D. (2002). Robust model based motion segmentation. Proceedings - International Conference on Pattern Recognition, 16(2), 753-756. Scopus7 WoS5
2001	Liang, J., Phillips, I., & Haralick, R. (2001). Performance evaluation of document structure extraction algorithms. Computer Vision and Image Understanding, 84(1), 144-159. DOI Scopus17
2001	Tissainayagam, P., & Suter, D. (2001). Visual tracking with automatic motion model switching. Pattern Recognition, 34(3), 641-660. DOI Scopus12 WoS11
2001	Tissainayagam, P., & Suter, D. (2001). Performance prediction analysis of a point feature tracker based on different motion models. COMPUTER VISION AND IMAGE UNDERSTANDING, 84(1), 104-125. DOI WoS3
2000	Suter, D., & Chen, F. (2000). Left ventricular motion reconstruction based on elastic vector splines. IEEE Transactions on Medical Imaging, 19(4), 295-305. DOI Scopus35 WoS38 Europe PMC13
1999	Bab-Hadiashar, A., & Suter, D. (1999). Robust segmentation of visual data using ranked unbiased scale estimate. Robotica, 17(6), 649-660. DOI Scopus65 WoS54
1999	Chen, F., & Suter, D. (1999). DIV-CURL vector quasi-interpolation on a finite domain. Mathematical and Computer Modelling, 30(1-2), 179-204. DOI Scopus1 WoS2
1998	Bab-Hadiashar, A., & Suter, D. (1998). Robust Optic Flow Computation. International Journal of Computer Vision, 29(1), 59-77. DOI Scopus109 WoS84
1998	Chen, F., & Suter, D. (1998). Fast Evaluation of Vector Splines in Three Dimensions. Computing (Vienna/New York), 61(3), 189-213. DOI Scopus2 WoS3
1998	Chen, F., & Suter, D. (1998). Using a fast multipole method to accelerate spline evaluations. IEEE computational science & engineering, 5(3), 24-31. DOI Scopus7 WoS6
1991	Suter, D. (1991). Constraint Networks in Vision. IEEE Transactions on Computers, 40(12), 1359-1367. DOI Scopus7 WoS4
1990	Deng, X., Dillon, T., Lew, K., Rankin, J., Smith, E., & Suter, D. (1990). Optimal topologies of transputers for different classes of problems. Computer Systems Science and Engineering, 5(1), 36-41.
1989	Suter, D., Deng, X., Cohen, H., & Dillon, T. (1989). Development and implementation of parallel vision algorithms. Technical Paper - Society of Manufacturing Engineers. MS.

Books

Year	Citation
2017	Chin, T. -J., & Suter, D. (2017). The Maximum Consensus Problem Recent Algorithmic Advances. USA: Morgan & Claypool Publishers.
2011	Suter, D., Fukui, K., & Tamaki, T. (2011). Introduction to the third international workshop on subspace methods (Vol. 6468 LNCS).
2000	Bab-Hadiashar, A., & Suter, D. (2000). Data Segmentation and Model Selection for Computer Vision A Statistical Approach. Springer Science & Business Media.

Book Chapters

Year	Citation
2019	Zhang, Z., Suter, D., & Tian, Y. (2019). Preface. In Z. Zhang, D. Suter, Y. Tian, A. B. Albu, N. Sidère, & H. J. Escalante (Eds.), Pattern Recognition and Information Forensics (Vol. 11188 LNCS, pp. V-VI).
2009	Tangkuampien, T., & Suter, D. (2009). KSM based machine learning for markerless motion capture. In L. Wang, L. Cheng, & G. Zhao (Eds.), Machine learning for human motion analysis: theory and practice (pp. 74-106). IGI Global. DOI
2004	Suter, D., & Wang, H. (2004). Robust fitting using mean shift: Applications in computer vision. In M. Hubert, G. Pison, A. Struyf, & S. V. Aelst (Eds.), Theory and Applications of Recent Robust Methods: Statistics for Industry and Technology (1 ed., pp. 307-318). Berlin: Birkhauser. WoS3

Conference Papers

Year	Citation
2018	Cai, Z., Chin, T., Le, H., & Suter, D. (2018). Deterministic consensus maximization with biconvex programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11216 LNCS (pp. 699-714). Munich. DOI Scopus1
2017	Zhang, Q., Chin, T., & Suter, D. (2017). Quasiconvex Plane Sweep for Triangulation with Outliers. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2017-October (pp. 920-928). Venice, ITALY: IEEE. DOI Scopus1 WoS1
2017	Williams, J., Carneiro, G., & Suter, D. (2017). Region of interest autoencoders with an application to pedestrian detection. In Y. Guo, H. Li, W. Cai, M. Murshed, Z. Wang, J. Gao, & D. Feng (Eds.), Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA 2017) Vol. 2017-December (pp. 580-587). Piscataway, NJ: IEEE. DOI
2017	Le, H., Chin, T., & Suter, D. (2017). RATSAC - Random tree sampling for maximum consensus estimation. In Y. Guo, H. Li, W. Cai, M. Murshed, Z. Wang, J. Gao, & D. Feng (Eds.), Proceedings DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications Vol. 2017-December (pp. 1-8). Sydney: IEEE. DOI
2017	Le, H., Chin, T. -J., & Suter, D. (2017). An exact penalty method for locally convergent maximum consensus. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 379-387). Online: IEEE. DOI Scopus5 WoS2
2016	Xiao, G., Wang, H., Yan, Y., & Suter, D. (2016). Superpixel-based two-view deterministic fitting for multiple-structure data. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Proceedings of the 14th European Conference on Computer Vision Vol. 9910 (pp. 517-533). Amsterdam, Netherlands: Springer International Publishing AG. DOI Scopus6 WoS4
2016	Le, H., Chin, T., & Suter, D. (2016). Conformal surface alignment with optimal Möbius search. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops Vol. 2016-December (pp. 2507-2516). Las Vegas, NV: IEEE. DOI Scopus2 WoS1
2015	Chin, T., Purkait, P., Eriksson, A., & Suter, D. (2015). Efficient globally optimal consensus maximisation with tree search. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 2413-2421). Boston, MA: IEEE. DOI Scopus20 WoS14
2015	Hadian-Jazi, M., Bab-Hadiashar, A., Hoseinnezhad, R., & Suter, D. (2015). Theoretical analysis of hough transform optimal cell size: Segmentation of nearby lines. In R. Jennane (Ed.), Image Processing, Theory, Tools and Applications (pp. 163-168). Orleans, France: IEEE. DOI
2015	Wang, H., Xiao, G., Yan, Y., & Suter, D. (2015). Mode-Seeking on Hypergraphs for Robust Geometric Model Fitting. In Proceedings of the IEEE International Conference on Computer Vision Vol. Proceedings 2015 IEEE International Conference on Computer Vision (pp. 2902-2910). Santiago, Chile: IEEE. DOI Scopus18 WoS13
2014	Chin, T. J., Parra Bustos, A., Brown, M. S., & Suter, D. (2014). Fast rotation search for real-time interactive point cloud registration. In I3D '14 - Symposium on Interactive 3D Graphics and Games (pp. 55-62). San Francisco, CA, USA: ACM. DOI Scopus2
2014	Lin, G., Shen, C., Shi, Q., Van Den Hengel, A., & Suter, D. (2014). Fast supervised hashing with decision trees for high-dimensional data. In Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1971-1978). Columbus, Ohio: IEEE. DOI Scopus200 WoS76
2014	Purkait, P., Chin, T. J., Ackermann, H., & Suter, D. (2014). Clustering with hypergraphs: the case for large hyperedges. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision - ECCV 2014, 13th European Conference, Zurich, Switzerland, September 6-12, 2014: Proceedings, Part IV Vol. 8692 LNCS (pp. 672-687). Zurich, Switzerland: Springer International Publishing. DOI Scopus18 WoS12
2014	Bustos, Á., Chin, T., & Suter, D. (2014). Fast rotation search with stereographic projections for 3D registration. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3930-3937). Columbus, OH: IEEE. DOI Scopus16 WoS11
2013	Lin, G., Shen, C., Suter, D., & Van Den Hengel, A. (2013). A general two-step approach to learning-based hashing. In Proceedings of the 2013 IEEE International Conference on Computer Vision, ICCV 2013 (pp. 1-13). USA: IEEE Computer Society. DOI Scopus104 WoS58
2013	Tennakoon, R., Bab-Hadiashar, A., Suter, D., & Cao, Z. (2013). Robust data modelling using thin plate splines. In Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013 (pp. 268-275). United States: IEEE. DOI Scopus2
2013	Sathyan, T., Chin, T. J., Suter, D., & Hedley, M. (2013). Improved wireless tracking using radio frequency and video sensors. In Proceedings of the16th International Conference of Information Fusion, FUSION 2013 (pp. 1442-1449). Online: IEEE. Scopus3 WoS1
2013	Liu, W., Chin, T. J., Carneiro, G., & Suter, D. (2013). Point correspondence validation under unknown radial distortion. In Proceedings of the IEEE2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013 (pp. 1-8). USA: IEEE. DOI Scopus1
2013	Hernandez Zaragoza, J., Chin, T., Brown, M., & Suter, D. (2013). As-projective-as-possible image stitching with moving DLT. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2339-2346). United States of America: IEEE. DOI Scopus116 WoS71
2013	Lovell, B., & Suter, D. (2013). Message from the general co-chairs. In 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. DOI
2012	Lin, G., Shen, C., Van Den Hengel, A., & Suter, D. (2012). Fast training of effective multi-class boosting using coordinate descent optimization. In Proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012 Vol. 7725 LNCS (pp. 782-793). Germany: Springer-Verlag. DOI
2012	Zhou, X., Li, X., Chin, T., & Suter, D. (2012). Superpixel-driven level set tracking. In Proceedings of the IEEE 19th International Conference on Image Processing, ICIP 2012 (pp. 409-412). USA: IEEE. DOI Scopus12 WoS6
2012	Tran, Q., Chin, T. J., Carneiro, G., Brown, M., & Suter, D. (2012). In defence of RANSAC for outlier rejection in deformable registration. In Proceedings of the12th European Conference on Computer Vision, ECCV 2012 Vol. 7575 LNCS (pp. 274-287). Germany: Springer-Verlag. DOI Scopus31 WoS21
2012	Zhou, X., Li, X., Chin, T., & Suter, D. (2012). Adaptive human silhouette reconstruction based on the exploration of temporal information. In Proceedings of the 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 (pp. 1005-1008). USA: IEEE. DOI Scopus1 WoS1
2012	Pham, T., Chin, T., Yu, J., & Suter, D. (2012). The random cluster model for robust geometric fitting. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 (pp. 710-717). USA: IEEE. DOI Scopus24 WoS11
2011	Wong, H., Chin, T., Yu, J., & Suter, D. (2011). Dynamic and hierarchical multi-structure geometric model fitting. In Proceedings of the 2011 IEEE International Conference on Computer Vision (pp. 1044-1051). USA: IEEE. DOI Scopus61 WoS36
2011	Pham, T., Chin, T., Yu, J., & Suter, D. (2011). Simultaneous sampling and multi-structure fitting with adaptive reversible jump MCMC. In Proceedings of the 25th Annual Conference on Neural Information Processing Systems (pp. 1-9). Spain: NIPS Foundation. Scopus9
2011	Hoseinnezhad, R., Vo, B. N., Vo, B. T., & Suter, D. (2011). Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter. In Proceedings of ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 2300-2303). USA: IEEE. DOI Scopus32 WoS22
2011	Yu, J., Chin, T. J., & Suter, D. (2011). A global optimization approach to robust multi-model fitting. In Proceedings of 2011 IEEE Conferencec on Computer Vision and Pattern Recognition (pp. 2041-2048). 345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE. DOI Scopus38 WoS5
2011	Yu, J., Eriksson, A., Chin, T., & Suter, D. (2011). An adversarial optimization approach to efficient outlier removal. In 2011 IEEE International Conference on Computer Vision (pp. 399-406). 345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE. DOI Scopus16 WoS7
2010	Zaidi, N., Squire, D., & Suter, D. (2010). BoostML: An adaptive metric learning for nearest neighbor classification. In Proceedings of the 14th PAKDD Vol. 6118 LNAI (pp. 142-149). Germany: Springer-Verlag. DOI
2010	Zaidi, N., Squire, D., & Suter, D. (2010). A gradient-based metric learning algorithm for k-NN classifiers. In 23rd Australasian Joint Conference on Artificial Intelligence, AI 2010 Vol. 6464 LNAI (pp. 194-203). Netherlands: Springer Verlag. DOI Scopus2 WoS2
2010	Wong, H., Chin, T. J., Yu, J., & Suter, D. (2010). Efficient multi-structure robust fitting with incremental top-k lists comparison. In Proceedings of The 10th Asian conference on computer vision (ACCV 2010) Vol. 6495 LNCS (pp. 1-12). www: Springer. DOI Scopus7 WoS1
2010	Li, L., Wang, H., Chin, T. J., Suter, D., & Zhang, S. (2010). Retrieving 3D CAD models using 2D images with optimized weights. In Proceedings of 2010 3rd International Congress on Image and Signal Processing, CISP 2010 Vol. 4 (pp. 1586-1589). USA: IEEE. DOI Scopus6
2010	Chin, T. J., Suter, D., & Wang, H. (2010). Multi-structure model selection via kernel optimisation. In Proceedings of 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (pp. 3586-3593). 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA: IEEE COMPUTER SOC. DOI Scopus10 WoS8
2010	Wang, H., Chin, T. J., & Suter, D. (2010). Visual localization and segmentation based on foreground/background modeling. In Proceedings of 2010 IEEE International Conference on Acoustics, speech and signal processing (pp. 1-4). USA: IEEE. DOI
2010	Chin, T., Yu, J., & Suter, D. (2010). Accelerated hypothesis generation for multi-structure robust fitting. In Proceedings of ECCV 2010 Vol. 6315 (pp. 533-546). Germany: Springer-Verlag Berlin. DOI Scopus21 WoS16
2010	Hoseinnezhad, R., Vo, B., Suter, D., & Vo, B. (2010). Multi-object filtering from image sequence without detection. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 1154-1157). Dallas, TX: IEEE. DOI Scopus24 WoS17
2009	Chin, T., & Suter, D. (2009). Keypoint induced distance profiles for visual recognition. In Proceedings of the 2009 Conference on Computer Vision & Recognition Vol. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1239-1246). USA: IEEE. DOI Scopus1
2009	Vo, B. N., Vo, B. T., Suter, D., & Pham, N. (2009). Bayesian multi-object estimation from image observations. In Proceedings of the 12th International Conference on Information Fusion (pp. 890-891). USA: IEEE. Scopus14 WoS8
2009	Chin, T. J., Wang, H., & Suter, D. (2009). The ordered residual kernel for robust motion subspace clustering. In Proceedings of NIPS 2009 (pp. 333-342). online: NIPS. Scopus24
2009	Hoseinnezhad, R., Vo, B., & Suter, D. (2009). Fast single-view people tracking. In Proceedings of COGIS'09 (pp. 1-6). CDROM: SEE.
2009	Hoseinnezhad, R., Vo, B., & Suter, D. (2009). Fast segmentation of multiple motions. In Proceedings of COGIS'09 (pp. 1-6). CDROM: SEE.
2009	Chin, T. J., Wang, H., & Suter, D. (2009). Robust Fitting of Multiple Structures: The Statistical Learning Approach. In Proceedings of The Twelfth IEEE International Conference on Computer Vision (pp. 413-420). USA: IEEE. DOI Scopus71 WoS43
2008	Lim, E., Suter, D., & Kocbek, S. (2008). Unsupervised plane data clustering based on modified Dirichlet Process Mixture Model method. In Proceedings of the 8th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2008 (pp. 148-155).
2008	Effendi, S., Jarvis, R., & Suter, D. (2008). Robot manipulation grasping of recognized objects for assistive technology support using stereo vision. In Proceedings of the 2008 Australasian Conference on Robotics and Automation, ACRA 2008. Scopus7
2008	Lim, E., & Suter, D. (2008). Multi-scale conditional random fields for over-segmented irregular 3D point clouds classification. In Computer Vision and Pattern Recognition Workshops (CVPRW) 2008 (pp. 7 pages). Online: IEEE. DOI Scopus18 WoS2
2008	Zhou, H., & Suter, D. (2008). Improved building detection by gaussian processes classification via feature space rescale and spectral kernel selection.. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008 (pp. 1-6). Online: IEEE. DOI Scopus3
2008	Zhou, H., Wang, L., & Suter, D. (2008). Human motion recognition using gaussian processes classification. In The 19th International Conference on Pattern Recognition (ICPR) 2008 (pp. 1-4). Online: IEEE. Scopus5
2008	Zhou, H., & Suter, D. (2008). Improving gaussian processes classification by spectral data reorganizing. In The 19th International Conference on Pattern Recognition (ICPR) 2008 (pp. 1-4). Online: IEEE. DOI Scopus2
2008	Shaji, A., Chandran, S., & Suter, D. (2008). Manifold optimisation for motion factorisation. In Proceedings of the19th International Conference on Pattern Recognition (ICPR 2008) (pp. 3555-3558). Tampa, USA: IEEE. DOI Scopus5
2008	Zaidi, N., & Suter, D. (2008). Confidence rated boosting algorithm for generic object detection. In The 19th International Conference on Pattern Recognition (ICPR) 2008 (pp. 1-4). Online: IEEE. DOI Scopus3
2008	Zaidi, N., & Suter, D. (2008). Object detection using a cascade of classifiers. In Digital Image Computing: Techniques and Applications (DICTA) 2008 Proceedings (pp. 600-605). Online: IEEE. DOI
2008	Effendi, S., Jarvis, R., & Suter, D. (2008). Fast stereo with background removal using phase correlation. In Image and Vision Computing New Zealand 2008 (pp. 1-6). Online: IEEE. DOI
2007	Wang, L., & Suter, D. (2007). Recognizing human activities from silhouettes: Motion subspace and factorial discriminative graphical model.. In IEEE Computer Vision and Pattern Recognition (CVPR) 2007 Proceedings (pp. 1-8). Online: IEEE. DOI Scopus154
2007	Cheong, J., Faggian, N., Langs, G., Suter, D., & Cicuttini, F. (2007). A comparision of Model-based methods for knee cartilage segmentation. In VISAPP 2007 - 2nd International Conference on Computer Vision Theory and Applications, Proceedings Vol. IFP (pp. 290-295). Scopus1
2007	Chin, T. J., Wang, L., Schindler, K., & Suter, D. (2007). Extrapolating learned manifolds for human activity recognition. In Proceedings of the 14th IEEE International Conference on Image Processing, 2007, San Antonio, Texas, USA. Vol. 1 (pp. 381-384). Online: IEEE. DOI Scopus15 WoS6
2007	Cheong, J., Faggian, N., Suter, D., & Cicuttini, F. (2007). Automatic segmentation of human tibial cartilage. In The Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications SPPRA 2007 Proceedings (pp. 368-373). Calgary, Canada: ACTA Press. Scopus2
2007	Zhou, H., & Suter, D. (2007). Fast sparse gaussian processes learning for man-made structure classification. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2007 Online Learning for Classification Workshop (pp. 1-6). Online: IEEE. DOI Scopus1
2007	Zhou, H., & Suter, D. (2007). Man-made structure segmentation using gaussian procesess and wavelet features.. In IEEE International Conference on Image Processing (ICIP) 2007 Proceedings Vol. 4 (pp. IV-349-IV-352). Online: IEEE. DOI
2007	Shaji, A., Siddiquie, B., Chandran, S., & Suter, D. (2007). Human pose extraction from monocular videos using constrained non-rigid factorization. In British Machine Vision Conference 2007 Proceedings (pp. 10 pages). Online: British Machine Vision Association. DOI Scopus1
2007	Lim, E., & Suter, D. (2007). Conditional random field for 3D point clouds with adaptive data reduction.. In 2007 International Conference on Cyberworlds Proceedings (pp. 404-408). Online: IEEE. DOI Scopus25 WoS3
2007	Zhou, H., & Suter, D. (2007). Man-made structure segmentation using Gaussian processes and wavelet features. In 2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-7 (pp. 2045-2048). San Antonio, TX: IEEE.
2007	Wang, L., Li, Y., Wang, C., & Zhang, H. (2007). Face recognition using gaborface-based 2DPCA and (2D)(2)PCA classification with ensemble and multichannel model. In 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN SECURITY AND DEFENSE APPLICATIONS (pp. 1-+). Honolulu, HI: IEEE. WoS80
2006	Yamamoto, K., Yendo, T., Fujii, T., Tanimoto, M., & Suter, D. (2006). Color correction for multi-camera system by using correspondences. In ACM SIGGRAPH 2006 Research Posters, SIGGRAPH 2006. DOI Scopus4
2006	Tangkuampien, T., & Suter, D. (2006). Real-time human pose inference using kernel principal component pre-image approximations. In British Machine Vision Conference BMVC2006 (pp. 10 pages). Online: The British Machine Vision Association. Scopus11
2006	Zhou, H., & Suter, D. (2006). A compact architecture for wireless video surveillance over cdma network. In International Conference on Advanced Video and Signal-based Surveillance, 2006 Proceedings (pp. 102-106). Online: IEEE. DOI Scopus3
2006	Wang, L., & Suter, D. (2006). Analyzing human movements from silhouettes using manifold learning. In Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (AVSS'06) (pp. 1-6). Online: IEEE. DOI Scopus22
2006	Hoseinnezhad, R., Bab-Hadiashar, A., & Suter, D. (2006). Finite sample bias of robust scale estimators in computer vision problems.. In International Symposium on Visual Computing 2006 Lecture Notes in Computer Science vol 4291 Vol. 4291 LNCS - I (pp. 445-454). Berlin: Springer Verlag. DOI Scopus9 WoS8
2006	Gobara, M., & Suter, D. (2006). Feature detection with an improved anisotropic filter.. In 7th Asian Conference on Computer Vision 2006 Lecture Notes in Computer Science vol 3852 Vol. 3852 LNCS (pp. 643-652). Berlin: Springer. DOI Scopus2 WoS1
2006	Wang, L., & Suter, D. (2006). Informative shape representations for human action recognition. In Proceedings 18th International Conference on Pattern Recognition 2006, volume 2 Vol. 2 (pp. 1266-1269). Online: IEEE. DOI Scopus46 WoS14
2006	Tangkuampien, T., & Suter, D. (2006). Human motion de-noising via greedy kernel principal component analysis filtering. In Proceedings 18th International Conference on Pattern Recognition 2006, volume 3, Vol. 3 (pp. 457-460). Online: IEEE. DOI Scopus18 WoS7
2006	Tangkuampien, T., & Suter, D. (2006). 3D object pose inference via kernel principal component analysis with image euclidian distance (IMED).. In British Machine Vision Conference BMVC2006 Proceedings (pp. 10 pages). Online: British Machine Vision Association. Scopus4
2006	Wang, H., Suter, D., & Schindler, K. (2006). Effective Appearance Model and Similarity Measure for Particle Filtering and Visual Tracking. In ECCV 2006, 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006, Proceedings (Lecture Notes in Computer Science vol 3953) Vol. 3953 LNCS (pp. 606-618). Berlin: Springer. DOI Scopus29 WoS13
2006	Wang, H., & Suter, D. (2006). A novel robust statistical method for background initialization and visual surveillance. In LECTURE NOTES IN COMPUTER SCIENCE, 7th Asian Conference on Computer Vision (ACCV) 2006, Vol. 3851 Vol. 3851 LNCS (pp. 328-337). Berlin: Springer. DOI Scopus35 WoS28
2006	Wang, H., & Suter, D. (2006). Background Subtraction Based on a Robust Consensus Method. In 18th International Conference on Pattern Recognition (ICPR), 2006, Volume 1 Vol. 1 (pp. 223-226). Online: IEEE. DOI Scopus54 WoS32
2006	Wang, H., & Suter, D. (2006). Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues. In 18th International Conference on Pattern Recognition (ICPR), 2006 Vol. 4 (pp. 892-895). Online: IEEE. DOI Scopus25 WoS9
2006	Chin, T. J., & Suter, D. (2006). A new distance criterion for face recognition using image sets. In P. J. Narayanan, S. K. Nayar, & H. Y. Shum (Eds.), Computer Vision - ACCV 2006: 7th Asian Conference on Computer Vision Vol. 3851 LNCS (pp. 549-558). Berlin: Springer-Verlag. DOI Scopus4 WoS2
2006	Chin, T., Schindler, K., & Suter, D. (2006). Incremental Kernel SVD for Face Recognition with Image Sets. In Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, 2006, Southampton, U.K. Vol. 2006 (pp. 461-466). Online: IEEE. DOI Scopus45 WoS24
2006	Chin, T. J., & Suter, D. (2006). Incremental Kernel PCA for Efficient Non-linear Feature Extraction. In Proceedings of the 17th British Machine Vision Conference, 2006, Edinburgh, U.K. (pp. 939-948). Online: The british Machine Vision Association. Scopus12
2006	Chin, T., & Suter, D. (2006). Improving the Speed of Kernel PCA on Large Scale Datasets. In Proceedings of the IEEE International Conference on Advanced Video and Signal based Surveillance, 2006, Sydney, NSW, Australia. (pp. 1-6). Online: IEEE. DOI Scopus5
2005	Wang, H., & Suter, D. (2005). Background Initialization with A New Robust Statistical Approach. In IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS) 2005 Vol. 2005 (pp. 153-159). Online: IEEE. DOI Scopus5
2005	Wang, H., & Suter, D. (2005). Tracking and segmenting people with occlusions by a sample consensus based method. In IEEE International Conference on Image Processing (ICIP), Genova, Italy 2005 Vol. 2 (pp. 410-413). Online: IEEE. DOI Scopus8 WoS1
2005	Wang, H., & Suter, D. (2005). A re-evaluation of mixture-of-Gaussian background modeling. In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Pennsylvania, USA, 2005 Vol. II (pp. 1017-1020). Online: IEEE. DOI Scopus48 WoS12
2005	Chin, T., U, J., Schindler, K., & Suter, D. (2005). Face Recognition from Video by Matching Image Sets. In Proceedings of Digital Image Computing: Techniques and Applications, 2005, Cairns, Queensland, Australia. Vol. 2005 (pp. 1-7). Online: IEEE. DOI Scopus9
2005	Cheong, J., Suter, D., & Cicuttini, F. (2005). Development of semi-automatic segmentation methods for measuring tibial cartilage volume.. In Proceedings Digital Image Computing: Techniques and Applications, Cairns, Australia 2005 (pp. 45-52). Online: IEEE. Scopus6
2005	Schindler, K., & Suter, D. (2005). Two-view multibody structure-and-motion with outliers. In Proceedings IEEE Conference in Computer Vision and Pattern Recognition, CVPR2005 Vol. II (pp. 676-683). Online: IEEE. DOI Scopus10 WoS3
2005	Cheong, J., Suter, D., & Cicuttini, F. (2005). A semi-automatic system for measuring tibial cartilage volume. In IEEE Tencon 2005 Proceedings Vol. 2007 (pp. 6 pages). Online: IEEE. DOI Scopus3
2004	Chen, P., & Suter, D. (2004). Shift-invariant wavelet denoising using interscale dependency. In Proceedings International Conference on Image Processing (ICIP) 2004 Volume 2 Vol. 5 (pp. 1005-1008). Online: IEEE. Scopus5 WoS2
2004	Wang, H., & Suter, D. (2004). Robust Fitting by Adaptive-Scale Residual Consensus. In LECTURE NOTES IN COMPUTER SCIENCE, European Conference on Computer Vision (ECCV) 2004 (LNCS vol 3023) Vol. 3023 (pp. 107-118). Berlin: Springer. DOI Scopus13 WoS3
2004	Georgescu, B., Comaniciu, D., Han, T., & Zhou, X. (2004). Multi-model component-based tracking using robust information fusion. In D. Comaniciu, K. Kanatani, R. Mester, & D. Suter (Eds.), STATISTICAL METHODS IN VIDEO PROCESSING Vol. 3247 (pp. 61-70). Prague, CZECH REPUBLIC: SPRINGER-VERLAG BERLIN. WoS4
2004	Georgescu, B., Comaniciu, D., Han, T., & Zhou, X. (2004). Multi-model component-based tracking using robust information fusion. In D. Comaniciu, K. Kanatani, R. Mester, & D. Suter (Eds.), STATISTICAL METHODS IN VIDEO PROCESSING Vol. 3247 (pp. 61-70). Prague, CZECH REPUBLIC: SPRINGER-VERLAG BERLIN. WoS4
2003	Wang, H., & Suter, D. (2003). Variable bandwidth QMDPE and its application in robust optic flow estimation. In 9th IEEE International Conference on Computer Vision (ICCV) 2003 Vol. 1 (pp. 178-183). Online: IEEE. Scopus20 WoS8
2003	Suter, D., Chen, P., & Wang, H. (2003). Extracting motion from images: Robust optic flow and structure from motion. In Proceedings Australia-Japan Advanced Workshop on Computer Vision, Adelaide 2003 (pp. 64-69). Adelaide: CS Press.
2003	Wang, H., & Suter, D. (2003). A model-based range image segmentation algorithm using a novel robust estimator. In 3rd International Workshop on Statistical and Computational Theories of Vision - SCTV (in conjunction with ICCV03), Nice, France, Oct. 2003 (pp. 21 pages). Washington: CS Press.
2003	Wang, H., & Suter, D. (2003). Color image segmentation using global information and local homogeneity. In International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2003 (pp. 89-98). Sydney: CSIRO Publishing.
2003	Wang, H., & Suter, D. (2003). False-peaks-avoiding mean shift method for unsupervised peak-valley sliding image segmentation. In International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2003 (pp. 581-590). Sydney: CSIRO Publishing.
2002	Boukir, S., & Suter, D. (2002). Application of rigid motion geometry to film restoration. In R. Kasturi, D. Laurendeau, & C. Suen (Eds.), Proceedings - International Conference on Pattern Recognition Vol. 16 (pp. 360-363). QUEBEC CITY, CANADA: IEEE COMPUTER SOC. Scopus2
2002	Wang, H., & Suter, D. (2002). LTSD: A Highly Efficient Symmetry-Based Robust Estimator. In Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002 (pp. 332-337). Scopus4
2002	Wang, H., & Suter, D. (2002). A Novel Robust Method for Large Numbers of Gross Errors. In Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002 (pp. 326-331). Scopus5
2002	David, S., Hamel, T., & Mahony, R. (2002). Visual servo control using homography estimation for the stabilization of an X4-flyer. In Proceedings of the IEEE Conference on Decision and Control Vol. 3 (pp. 2872-2877). LAS VEGAS, NV: IEEE. Scopus25 WoS12
2000	Tissainayagam, P., & Suter, D. (2000). Visual tracking of multiple objects with automatic motion model switching. In A. Sanfeliu, J. Villanueva, M. Vanrell, R. Alquezar, T. Huang, & J. Serra (Eds.), Proceedings - International Conference on Pattern Recognition Vol. 3 (pp. 1134-1141). BARCELONA, SPAIN: IEEE COMPUTER SOC. DOI
1998	Bab-Hadiashar, A., & Suter, D. (1998). Robust range segmentation. In A. Jain, S. Venkatesh, & B. Lovell (Eds.), FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 (pp. 969-971). BRISBANE, AUSTRALIA: IEEE COMPUTER SOC. WoS1
1998	Tissainayagam, P., & Suter, D. (1998). Visual tracking and motion determination using the IMM algorithm. In A. K. Jain, S. Venkatesh, & B. C. Lovell (Eds.), FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 (pp. 289-291). BRISBANE, AUSTRALIA: IEEE COMPUTER SOC. WoS3
1998	Chen, F., & Suter, D. (1998). Image coordinate transformation based on DTV-CURL vector splines. In A. K. Jain, S. Venkatesh, & B. C. Lovell (Eds.), FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 (pp. 518-520). BRISBANE, AUSTRALIA: IEEE COMPUTER SOC. WoS1
1998	Tissainayagam, P., & Suter, D. (1998). Visual Feature Tracking with Automatic Motion Model Switching. In Proceedings of the Joint Conference on Information Sciences Vol. 4 (pp. 322-325). Scopus3
1998	Tissainayagam, P., & Suter, D. (1998). Object Tracking in Image Sequences using Multiple Hypothesis Approach. In Proceedings of the Joint Conference on Information Sciences Vol. 4 (pp. 473-475).
1997	Chen, F., & Suter, D. (1997). Elastic spline models for human cardiac motion estimation. In Proceedings of the IEEE Nonrigid and Articulated Motion Workshop (pp. 120-127). SAN JUAN, PR: I E E E, COMPUTER SOC PRESS. DOI Scopus7 WoS10
1997	Bab-Hadiashar, A., & Suter, D. (1997). Optical flow calculation using robust statistics. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 988-993). SAN JUAN, PR: I E E E, COMPUTER SOC PRESS. DOI Scopus12 WoS5
1997	Bab-Hadiashar, A., & Suter, D. (1997). Robust total least squares based optic flow computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 1351 (pp. 566-573). DOI Scopus4
1997	Chen, F., & Suter, D. (1997). Multiscale image representation and edge detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 1352 (pp. 49-56).
1997	Bab-Hadiashar, A., & Suter, D. (1997). Robust motion segmentation using rank ordering estimators. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 1352 (pp. 599-606). Scopus3
1996	Bab-Hadiashar, A., & Suter, D. (1996). Robust optic flow estimation using least median of squares. In P. Delogne (Ed.), IEEE International Conference on Image Processing Vol. 1 (pp. 513-516). LAUSANNE, SWITZERLAND: I E E E. Scopus9 WoS4
1996	Richardson, P., & Suter, D. (1996). Restoration of historic film for digital compression: a case study. In IEEE International Conference on Image Processing Vol. 2 (pp. 49-52). WASHINGTON, DC: I E E E, COMPUTER SOC PRESS. Scopus18
1995	Bab-Hadiashar, A., Suter, D., & Jarvis, R. (1995). 2D motion extraction using an image interpolation technique. In A. Tescher (Ed.), Proceedings of SPIE - The International Society for Optical Engineering Vol. 2564 (pp. 271-281). SAN DIEGO, CA: SPIE - INT SOC OPTICAL ENGINEERING. DOI Scopus3
1995	Wu, Y., & Suter, D. (1995). Historical film processing. In A. Tescher (Ed.), Proceedings of SPIE - The International Society for Optical Engineering Vol. 2564 (pp. 289-300). SAN DIEGO, CA: SPIE - INT SOC OPTICAL ENGINEERING. DOI Scopus8 WoS5
1995	Suter, D. (1995). Divergence-free wavelets made easy. In A. Laine, & M. Unser (Eds.), Proceedings of SPIE - The International Society for Optical Engineering Vol. 2569 (pp. 102-113). SAN DIEGO, CA: SPIE - INT SOC OPTICAL ENGINEERING. DOI Scopus2 WoS1
1994	Suter, D. (1994). Motion estimation and vector splines. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 939-942). SEATTLE, WA: I E E E, COMPUTER SOC PRESS. Scopus77 WoS60
1993	Suter, D. (1993). Mixed finite elements and Whitney forms for visual reconstruction. In B. Vemuri (Ed.), Proceedings of SPIE - The International Society for Optical Engineering Vol. 2031 (pp. 51-62). SAN DIEGO, CA: SPIE - INT SOC OPTICAL ENGINEERING. DOI Scopus2 WoS1
1993	Suter, D. (1993). Multipole methods for visual reconstruction. In B. Vemuri (Ed.), Proceedings of SPIE - The International Society for Optical Engineering Vol. 2031 (pp. 16-26). SAN DIEGO, CA: SPIE - INT SOC OPTICAL ENGINEERING. DOI Scopus2
1991	Suter, D. (1991). Generalization of the Harris 'coupled depth-slope' analog visual reconstruction network. In Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks (pp. 729-739). Scopus1
1991	Mansor, D., & Suter, D. (1991). Implementation of visual reconstruction networks--Alternatives to resistive networks. In 1991 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 (pp. 1898-1905). SINGAPORE, SINGAPORE: INST ELECTRICAL ENGINEERS.
1990	Suter, D., & Cohen, H. (1990). Incorporating knowledge via regularization theory: Applications in vision and image processing. In C. BARTER, & M. BROOKS (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 406 LNAI (pp. 379-394). ADELAIDE, AUSTRALIA: SPRINGER-VERLAG BERLIN. DOI
1988	Suter, D., & Deng, X. (1988). Neural net simulation on transputers. In Unknown Conference (pp. 694-697). Scopus2
1987	Suter, D. (1987). NEURAL NET SURFACE INTERPOLATION.. In Unknown Conference (pp. 118-123).

Conference Items

Year	Citation
2012	Suter, D., Chin, T. J., Wong, H. S., & Pham, T. T. (2012). Perception as hypothesis testing - how to discover and generate hypotheses. Poster session presented at the meeting of Abstracts of the 2012 Joint Applied Vision Association and British Machine Vision Association Annual Meeting, as published in Perception. Cambridge, United Kingdom: Pion. DOI

Grants Held in 2017

1.ARC Discovery Grant: DP160103490 Dr Tat-Jun Chin; Professor David Suter $268,000.00

2. ARC Linkage Grant: LP160100662 Professor Alireza Bab-Hadiashar; Professor David Suter; Dr Reza Hoseinnezhad; Mr Adrian Neugebauer $285,000.00 + industry contribution.

3. ARC Linkage Grant: LP160100495 Dr Tat-Jun Chin; Professor David Suter; Dr Matthew Tetlow $275,000.00 + industry contribution

Previous Grants:

Significant Competitive Grants (CI - Chief Investigator)
ARC Discovery Grant (CI) 2016-2018 “Optimal Robust Fitting under the Framework of LP-Type Problems”
ARC Discovery Grant (lead CI) 2013-2015 “Improved Image Analysis: Maximised Statistical Use of Geometry/Shape Constraints”
ARC Discovery Grant (sole CI) 2011-2013 “Computer Vision from a Multi- Structural Analysis Framework”
ARC LIEF Grant (one of 10 CI’s) 2010 “Accelerating Australia’s large scale video surveillance research programmes.”

ARC Discovery Grant (lead CI) 2008-2011 "Statistical Methods of Model Fitting and Segmentation in Computer Vision" (ranked in top 7% of applications)
ARC Discovery Grant (co-CI) 2008-2010 "Visual Tracking of Multiple Objects: A Stochastic Geometrical Approach"

ARC Discovery Grant (sole CI) 2004-06 “Visual Tracking: Geometric fitting and filtering
ARC funded Centre for Perceptive and Intelligent Machines in Complex Environments (2003-2008) (one of five Monash CI’s, two from Curtin, one from ANU and 4 from Melbourne).

ARC Research Network 2004 (one of about 50 CI's)
Large ARC 4 grants held: 1992 (sole CI), 1995 (sole CI), 1997 (sole CI), 2000 (as leading CI).
Small ARC 4 grants held: 1995 (sole CI), 1997 (sole CI), 1999 (sole CI), 2000 (sole CI).
ARC funded “Perceptive Systems Networks”
ARC IREX 2001 (lead CI)
ARC SPIRT 2001 (as leading CI)
ARC Linkage 2005 (as co-CI) "Data Fusion Techniques for Electro-Mechanical Braking Systems"
ARC Linkage 2013 (as co-CI) " Intelligent collision avoidance system for mobile industrial platforms”
Other External 1993 (ATERB sole), 1994 (ATERB sole), 1996 (Collier Foundation sole).
Internal 8 significant grants: 1989 (sole CI), 1996 (sole CI), 1999 (part-25%), 2000 (lead CI), 2001
(lead CI), 2002 (lead CI), 2003 (lead CI), 2004 (sole CI), 2004 (lead CI), 2005 (lead CI).

Total Income: National Competitive Grants >$12mAUD

Semester 1 2009 AI
Semester 2 2009 Computer Vision
Semester 1 2010 AI
Semester 2 2010 Computer Vision
Semester 1 2011 Computer Graphics
Semester 1 2011 AI @ Singapore Campus
Semester 2 2012 Systems Programming and C/C++
Semester 2 2013 Systems Programming and C/C++
Semester 1 2014 Computer Graphics
Semester 1 2016 Systems Programming, Solving Engineering Models, Computer Graphics @ Singapore Campus, AI @ Singapore Campus
Mid 2016 AI @ Harbin Institute of Technology
Tri(Quad)mester 1 2017 AI @ Singapore campus
Semmester 1 2017 Solving Engineering Models, and Scientifc Computing

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Current Higher Degree by Research Supervision (University of Adelaide)

Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
2019	Co-Supervisor	Pedestrian detection assisted by semi-supervised learning and exploring the link between regularization and compression	Master of Philosophy	Master	Full Time	Mr Jerome Oskar Williams
2016	Co-Supervisor	Registration of Image Data	Doctor of Philosophy	Doctorate	Full Time	Mr Zhipeng Cai

Past Higher Degree by Research Supervision (University of Adelaide)

Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
2015 - 2018	Co-Supervisor	Robust and Large-Scale Quasiconvex Programming in Structure-from-Motion	Doctor of Philosophy	Doctorate	Full Time	Mr Qianggong Zhang
2014 - 2016	Co-Supervisor	Maximum Consensus with Mixed Integer Linear Programming	Master of Philosophy	Master	Full Time	Mr Yang Heng Kee
2014 - 2018	Principal Supervisor	New Algorithmic Developments in Maximum Consensus Robust Fitting	Doctor of Philosophy	Doctorate	Full Time	Mr Huu Minh Le
2013 - 2017	Co-Supervisor	Moving Least Squares Registration in Computer Vision: New Applications and Algorithms	Doctor of Philosophy	Doctorate	Full Time	Mr Xiang Liu
2012 - 2016	Principal Supervisor	Robust Rotation Search in Computer Vision	Doctor of Philosophy	Doctorate	Full Time	Dr Alvaro Joaquin Parra Bustos
2011 - 2014	Co-Supervisor	Robust Parameter Estimation in Computer Vision: Geometric Fitting and Deformable Registration	Doctor of Philosophy	Doctorate	Full Time	Mr Quoc Huy Tran
2011 - 2015	Co-Supervisor	Learning Structured Prediction Models in Computer Vision	Doctor of Philosophy	Doctorate	Full Time	Miss Fayao Liu
2011 - 2014	Co-Supervisor	As-Projective-As-Possible Image Stitching with Moving DLT	Doctor of Philosophy	Doctorate	Full Time	Mr Julio Cesar Hernandez Zaragoza
2010 - 2014	Co-Supervisor	Structured Output Prediction and Binary Code Learning in Computer Vision	Doctor of Philosophy	Doctorate	Full Time	Dr Guosheng Lin
2010 - 2014	Co-Supervisor	Robust Estimation in Computer Vision: Optimisation Methods and Applications	Doctor of Philosophy	Doctorate	Full Time	Dr Trung Thanh Pham
2009 - 2013	Principal Supervisor	A Preference Analysis Approach to Robust Geometric Model Fitting in Computer Vision	Doctor of Philosophy	Doctorate	Full Time	Miss Hoi Wong

Position: Senior Lecturer
Phone: 83133661
Email: david.suter@adelaide.edu.au
Fax: 8313 4366
Campus: North Terrace
Building: Ingkarni Wardli, floor 4
Room: 4 22
Org Unit: School of Computer Science