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2013

Journal Article

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

Reddy, Vikas, Sanderson, Conrad and Lovell, Brian (2013). Improved foreground detection via block-based classifier cascade with probabilistic decision integration. IEEE Transactions On Circuits And Systems For Video Technology, 23 (1) 6213100, 83-93. doi: 10.1109/TCSVT.2012.2203199

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

2013

Conference Publication

Spatio-temporal covariance descriptors for action and gesture recognition

Sanin, Andres, Sanderson, Conrad, Harandi, Mehrtrash and Lovell, Brian (2013). Spatio-temporal covariance descriptors for action and gesture recognition. 2013 IEEE Workshop on Applications of Computer Vision, Tampa, FL, United States, 15-17 January 2013. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2013.6475006

Spatio-temporal covariance descriptors for action and gesture recognition

2013

Journal Article

Video surveillance: Past, present, and now the future

Porikli, Fatih, Bremond, Francois, Dockstader, Shiloh L., Ferryman, James, Hoogs, Anthony, Lovell, Brian C., Pankanti, Sharath, Rinner, Bernhard, Tu, Peter and Venetianer, Peter L. (2013). Video surveillance: Past, present, and now the future. IEEE Signal Processing Magazine, 30 (3) 6494685, 190-198. doi: 10.1109/MSP.2013.2241312

Video surveillance: Past, present, and now the future

2013

Book Chapter

Graph-embedding discriminant analysis on Riemannian manifolds for visual recognition

Shirazi, Sareh, Alavi, Azadeh, Harandi, Mehrtash T. and Lovell, Brian C. (2013). Graph-embedding discriminant analysis on Riemannian manifolds for visual recognition. Graph Embedding for Pattern Analysis. (pp. 157-176) edited by Yun Fu and Yunqian Ma. New York, NY, USA: Springer. doi: 10.1007/978-1-4614-4457-2

Graph-embedding discriminant analysis on Riemannian manifolds for visual recognition

2013

Journal Article

Equatorial westward electrojet impacting equatorial ionization anomaly development during the 6 April 2000 superstorm

Horvath, Ildiko and Lovell, Brian C. (2013). Equatorial westward electrojet impacting equatorial ionization anomaly development during the 6 April 2000 superstorm. Journal of Geophysical Research A: Space Physics, 118 (11), 7398-7409. doi: 10.1002/2013JA019311

Equatorial westward electrojet impacting equatorial ionization anomaly development during the 6 April 2000 superstorm

2013

Conference Publication

Non-linear stationary subspace analysis with application to video classification

Baktashmotlagh, Mahsa, Harandi, Mehrtash T., Bigdeli, Abbas, Lovell, Brian C. and Salzmann, Mathieu (2013). Non-linear stationary subspace analysis with application to video classification. 30th International Conference on Machine Learning, Atlanta, GA, United States, 16 - 21 June 2013. Germany: International Machine Learning Society (IMLS).

Non-linear stationary subspace analysis with application to video classification

2013

Journal Article

Kernel analysis on Grassmann manifolds for action recognition

Harandi, Mehrtash T., Sanderson, Conrad, Shirazi, Sareh and Lovell, Brian C. (2013). Kernel analysis on Grassmann manifolds for action recognition. Pattern Recognition Letters, 34 (15), 1906-1915. doi: 10.1016/j.patrec.2013.01.008

Kernel analysis on Grassmann manifolds for action recognition

2013

Conference Publication

Unsupervised domain adaptation by Domain Invariant Projection

Baktashmotlagh, Mahsa, Harandi, Mehrtash T., Lovell, Brian C. and Salzmann, Mathieu (2013). Unsupervised domain adaptation by Domain Invariant Projection. 2013 IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 1-8 December 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICCV.2013.100

Unsupervised domain adaptation by Domain Invariant Projection

2013

Book Chapter

Machine learning applications in computer vision

Harandi, Mehrtash, Taheri, Javid and Lovell, Brian C. (2013). Machine learning applications in computer vision. Image processing: Concepts, methodologies, tools, and applications. (pp. 896-926) edited by Mehdi Khosrow-Pour. Hershey, PA., United States: IGI Global. doi: 10.4018/978-1-4666-3994-2.ch045

Machine learning applications in computer vision

2013

Conference Publication

Classification of human epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors

Wiliem, Arnold, Wong, Yongkang, Sanderson, Conrad, Hobson, Peter, Chen, Shaokang and Lovell, Brian C. (2013). Classification of human epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors. 2013 IEEE Workshop on Applications of Computer Vision (WACV), Tampa, FL, United States, 15-17 Janunary 2013. Piscataway, NJ, USA: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2013.6475005

Classification of human epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors

2013

Conference Publication

Region-based anomaly localisation in crowded scenes via trajectory analysis and path prediction

Zhang, Teng, Wiliem, Arnold and Lovell, Brian C. (2013). Region-based anomaly localisation in crowded scenes via trajectory analysis and path prediction. 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013, Hobart, TAS, Australia, November 26, 2013-November 28, 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2013.6691519

Region-based anomaly localisation in crowded scenes via trajectory analysis and path prediction

2013

Conference Publication

Dictionary earning and sparse coding on Grassmann manifolds: an extrinsic solution

Harandi, Mehrtash, Sanderson, Conrad, Shen, Chunhua and Lovell, Brian C. (2013). Dictionary earning and sparse coding on Grassmann manifolds: an extrinsic solution. IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 1-8 December 2013. New York, NY United States: IEEE. doi: 10.1109/ICCV.2013.387

Dictionary earning and sparse coding on Grassmann manifolds: an extrinsic solution

2013

Book Chapter

Motion estimation in colour image sequences

Benois-Pineau, Jenny, Lovell, Brian C. and Andrews, Robert J. (2013). Motion estimation in colour image sequences. Advanced color image processing and analysis. (pp. 377-395) edited by Christine Fernandez-Maloigne. New York, NY, United States: Springer. doi: 10.1007/978-1-4419-6190-7_11

Motion estimation in colour image sequences

2013

Conference Publication

Improved image set classification via joint sparse approximated nearest subspaces

Chen, Shaokang, Sanderson, Conrad, Harandi, Mehrtash T and Lovell, Brian C. (2013). Improved image set classification via joint sparse approximated nearest subspaces. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013, Portland, OR United States, 23 - 28 June 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/CVPR.2013.65

Improved image set classification via joint sparse approximated nearest subspaces

2012

Journal Article

Shadow detection: A survey and comparative evaluation of recent methods

Sanin, Andres, Sanderson, Conrad and Lovell, Brian C. (2012). Shadow detection: A survey and comparative evaluation of recent methods. Pattern Recognition, 45 (4), 1684-1695. doi: 10.1016/j.patcog.2011.10.001

Shadow detection: A survey and comparative evaluation of recent methods

2012

Conference Publication

Combined learning of salient local descriptors and distance metrics for image set face verification

Sanderson, Conrad, Harandi, Mehrtash T., Wong, Yongkang and Lovell, Brian C. (2012). Combined learning of salient local descriptors and distance metrics for image set face verification. 9th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Beijing, Peoples R China, 18-21 September 2012. Los Alamitos, CA United States: I E E E Computer Society. doi: 10.1109/AVSS.2012.23

Combined learning of salient local descriptors and distance metrics for image set face verification

2012

Conference Publication

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

Harandi, Mehrtash T., Sanderson, Conrad, Wiliem, Arnold and Lovell, Brian C. (2012). Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures. 2012 IEEE Workshop on Applications of Computer Vision, Breckenridge, CO, United States, 9-11 January 2012. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2012.6163005

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

2012

Conference Publication

Improved person re-identification using statistical approximation

Yang, Yan, Dadgostar, Farhad, Mau, Sandra and Lovell, Brian C. (2012). Improved person re-identification using statistical approximation. 2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Fremantle, WA, Australia, 3-5 December 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2012.6411683

Improved person re-identification using statistical approximation

2012

Conference Publication

K-tangent spaces on Riemannian manifolds for improved pedestrian detection

Sanin, Andres, Sanderson, Conrad, Harandi, Mehrtash and Lovell, Brian C. (2012). K-tangent spaces on Riemannian manifolds for improved pedestrian detection. 2012 19th IEEE International Conference on Image Processing (ICIP), Orlando, United States, 30 September - 3 October 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICIP.2012.6466899

K-tangent spaces on Riemannian manifolds for improved pedestrian detection

2012

Book Chapter

Machine learning applications in computer vision

Harandi, Mehrtash, Taheri, Javid and Lovell, Brian C. (2012). Machine learning applications in computer vision. Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques. (pp. 99-132) Hershey, Pennsylvania, USA: IGI Global. doi: 10.4018/978-1-4666-1833-6.ch007

Machine learning applications in computer vision