| Going deeper into action recognition: A survey S Herath, M Harandi, F Porikli Image and vision computing 60, 4-21, 2017 | 427 | 2017 |
| Unsupervised domain adaptation by domain invariant projection M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann Proceedings of the IEEE International Conference on Computer Vision, 769-776, 2013 | 351 | 2013 |
| Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching MT Harandi, C Sanderson, S Shirazi, BC Lovell CVPR 2011, 2705-2712, 2011 | 305 | 2011 |
| Kernel methods on the Riemannian manifold of symmetric positive definite matrices S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 276 | 2013 |
| Sparse coding and dictionary learning for symmetric positive definite matrices: A kernel approach MT Harandi, C Sanderson, R Hartley, BC Lovell European Conference on Computer Vision, 216-229, 2012 | 198 | 2012 |
| Spatio-temporal covariance descriptors for action and gesture recognition A Sanin, C Sanderson, MT Harandi, BC Lovell 2013 IEEE Workshop on applications of Computer Vision (WACV), 103-110, 2013 | 184 | 2013 |
| From manifold to manifold: Geometry-aware dimensionality reduction for SPD matrices MT Harandi, M Salzmann, R Hartley European conference on computer vision, 17-32, 2014 | 173 | 2014 |
| Kernel methods on Riemannian manifolds with Gaussian RBF kernels S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi IEEE transactions on pattern analysis and machine intelligence 37 (12), 2464 …, 2015 | 151 | 2015 |
| Dictionary learning and sparse coding on Grassmann manifolds: An extrinsic solution M Harandi, C Sanderson, C Shen, BC Lovell Proceedings of the IEEE international conference on computer vision, 3120-3127, 2013 | 134 | 2013 |
| Dimensionality reduction on SPD manifolds: The emergence of geometry-aware methods M Harandi, M Salzmann, R Hartley IEEE transactions on pattern analysis and machine intelligence 40 (1), 48-62, 2017 | 123 | 2017 |
| Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures MT Harandi, C Sanderson, A Wiliem, BC Lovell 2012 IEEE Workshop on the Applications of Computer Vision (WACV), 433-439, 2012 | 112 | 2012 |
| Bregman divergences for infinite dimensional covariance matrices M Harandi, M Salzmann, F Porikli Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 105 | 2014 |
| Domain adaptation on the statistical manifold M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 93 | 2014 |
| Learning an invariant hilbert space for domain adaptation S Herath, M Harandi, F Porikli Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 89 | 2017 |
| Improved image set classification via joint sparse approximated nearest subspaces S Chen, C Sanderson, MT Harandi, BC Lovell Proceedings of the IEEE Conference on Computer Vision and pattern …, 2013 | 89 | 2013 |
| Riemannian Coding and Dictionary Learning: Kernels to the Rescue M Harandi, M Salzmann IEEE Conference on Computer Vision and Pattern Recognition, 3926-3935, 2015 | 84 | 2015 |
| Expanding the family of grassmannian kernels: An embedding perspective MT Harandi, M Salzmann, S Jayasumana, R Hartley, H Li European Conference on Computer Vision, 408-423, 2014 | 81 | 2014 |
| Extrinsic methods for coding and dictionary learning on Grassmann manifolds M Harandi, R Hartley, C Shen, B Lovell, C Sanderson International Journal of Computer Vision 114 (2), 113-136, 2015 | 77 | 2015 |
| Fisher tensors for classifying human epithelial cells M Faraki, MT Harandi, A Wiliem, BC Lovell Pattern Recognition 47 (7), 2348-2359, 2014 | 71 | 2014 |
| Deep unsupervised saliency detection: A multiple noisy labeling perspective J Zhang, T Zhang, Y Dai, M Harandi, R Hartley Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 68 | 2018 |
Brian C. LovellProfessor, The University of QueenslandVerified email at itee.uq.edu.au
