Showing results 105 to 124 of 160
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| Preview | Issue Date | Title | Author(s) |
| 2009 | Measuring latency for video surveillance systems | Hill, R.; Madden, C.; Van Den Hengel, A.; Detmold, H.; Dick, A.; Shi, H.; Zhang, Y.C.; Bottema, M.J.; Lovell, B.C.; Maeder, A.J.; Digital Image Computing: Techniques and Applications (2009 : Melbourne, Australia) |
| 2015 | Mid-level deep pattern mining | Li, Y.; Liu, L.; Shen, C.; Van Den Hengel, A.; 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015) (7 Jun 2015 - 12 Jun 2015 : Boston, MA) |
| 2008 | Middleware for distributed video surveillance | Detmold, H.; Van Den Hengel, A.; Dick, A.; Falkner, K.; Munro, D.; Morrison, R. |
| 2006 | Middleware for video surveillance networks | Detmold, H.; Dick, A.; Falkner, K.; Munro, D.; Van Den Hengel, A.; Morrison, R.; Cahill, V.; Michiels, S.; International Workshop on Middleware for Sensor Networks (2006 : Melbourne, Australia) |
| 2009 | Multi-projective Parameter Estimation for Sets of Homogeneous Matrices | Chojnacki, W.; Hill, R.; Van Den Hengel, A.; Brooks, M.; Shi, H.; Zhang, Y.C.; Bottema, M.J.; Lovell, B.C.; Maeder, A.J.; Digital Image Computing: Techniques and Applications (2009 : Melbourne, Australia) |
| 2010 | Multiple homography estimation with full consistency constraints | Chojnacki, W.; Szpak, Z.; Brooks, M.; Van Den Hengel, A.; Zhang, J.; Shen, C.; Geers, G.; Digital Image Computing: Techniques and Applications (2010 : Sydney, Australia) |
| 2012 | Non-sparse linear representations for visual tracking with online reservoir metric learning | Li, X.; Shen, C.; Shi, Q.; Dick, A.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (25th : 2012 : Providence, Rhode Island) |
| 2013 | On the dimension of the set of two-view multi-homography matrices | Chojnacki, W.; Van Den Hengel, A. |
| 2000 | On the fitting of surfaces to data with covariances | Chojnacki, W.; Brooks, M.; Van Den Hengel, A.; Gawley, D. |
| 2016 | Online unsupervised feature learning for visual tracking | Liu, F.; Shen, C.; Reid, I.; Van Den Hengel, A. |
| 2009 | Optimization on the manifold of multiple homographies | Eriksson, A.; Van Den Hengel, A.; IEEE ICCV Workshops (12th : 2009 : Kyoto, Japan) |
| 2016 | Pairwise matching through max-weight bipartite belief propagation | Zhang, Z.; Shi, Q.; McAuley, J.; Wei, W.; Zhang, Y.; Van Den Hengel, A.; 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2016) (26 Jun 2016 - 1 Jul 2016 : Las Vegas, NV) |
| 2015 | Part-based modelling of compound scenes from images | Van Den Hengel, A.; Russell, C.; Dick, A.; Bastian, J.; Pooley, D.; Fleming, L.; Agapito, L.; IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (7 Jun 2015 - 12 Jun 2015 : Boston, MA) |
| 2017 | Part-based robust tracking using online latent structured learning | Yao, R.; Shi, Q.; Shen, C.; Zhang, Y.; Van Den Hengel, A. |
| 2013 | Part-based visual tracking with online latent structural learning | Yao, R.; Shi, Q.; Shen, C.; Zhang, Y.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (26th : 2013 : Portland, Oregon) |
| 2016 | Pedestrian detection with spatially pooled features and structured ensemble learning | Paisitkriangkrai, S.; Shen, C.; Van Den Hengel, A. |
| 2012 | Positive semidefinite metric learning using boosting-like algorithms | Shen, C.; Kim, J.; Wang, L.; Van Den Hengel, A. |
| 2009 | Positive Semidefinite Metric Learning with Boosting | Shen, C.; Kim, J.; Wang, L.; Van Den Hengel, A.; Annual Conference on Neural Information Processing Systems (23rd : 2009 : Vancouver, Canada) |
| 2007 | Preparing for post-catastrophe video processing | Van Den Hengel, A.; Detmold, H.; Dick, A.; Hill, R.; Priyan Mendis,; RNSA Security Technology Conference (3rd : 2007 : Melbourne, Vic.) |
| 2003 | Probabilistic multiple cue intergration for particle filter based tracking | Shen, C.; Van Den Hengel, A.; Dick, A.; Sun, C.; Talbot, H.; Ourselin, S.; Adriaansen, T.; Australian Pattern Recognition Society. Conference (7th : 2003 : Sydney, N.S.W.) |
