A review of visual tracking K Cannons Dept. Comput. Sci. Eng., York Univ., Toronto, Canada, Tech. Rep. CSE-2008-07 242, 2008 | 138 | 2008 |
Efficient action spotting based on a spacetime oriented structure representation KG Derpanis, M Sizintsev, K Cannons, RP Wildes 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 135 | 2010 |
Action spotting and recognition based on a spatiotemporal orientation analysis KG Derpanis, M Sizintsev, KJ Cannons, RP Wildes IEEE transactions on pattern analysis and machine intelligence 35 (3), 527-540, 2012 | 72 | 2012 |
Compositional models for video event detection: A multiple kernel learning latent variable approach A Vahdat, K Cannons, G Mori, S Oh, I Kim Proceedings of the IEEE International Conference on Computer Vision, 1185-1192, 2013 | 71 | 2013 |
Similarity constrained latent support vector machine: An application to weakly supervised action classification N Shapovalova, A Vahdat, K Cannons, T Lan, G Mori European Conference on Computer Vision, 55-68, 2012 | 62 | 2012 |
Multimedia event detection with multimodal feature fusion and temporal concept localization S Oh, S McCloskey, I Kim, A Vahdat, KJ Cannons, H Hajimirsadeghi, ... Machine vision and applications 25 (1), 49-69, 2014 | 55 | 2014 |
Visual tracking using a pixelwise spatiotemporal oriented energy representation KJ Cannons, JM Gryn, RP Wildes European Conference on Computer Vision, 511-524, 2010 | 48 | 2010 |
Signal classification through multifractal analysis and complex domain neural networks W Kinsner, V Cheung, K Cannons, J Pear, T Martin IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2006 | 45 | 2006 |
Spatiotemporal oriented energy features for visual tracking K Cannons, R Wildes Asian Conference on Computer Vision, 532-543, 2007 | 42 | 2007 |
An introduction to probabilistic neural networks V Cheung, K Cannons Retrieved August 2, 2011, 2003 | 41 | 2003 |
TRECVID 2012 GENIE: Multimedia event detection and recounting AGA Perera, S Oh, P Megha, T Ma, A Hoogs, A Vahdat, K Cannons, ... In TRECVID Workshop, 2012 | 39 | 2012 |
The applicability of spatiotemporal oriented energy features to region tracking KJ Cannons, RP Wildes IEEE transactions on pattern analysis and machine intelligence 36 (4), 784-796, 2013 | 26 | 2013 |
Spatiotemporal motion analysis for the detection and classification of moving targets DY Chen, K Cannons, HR Tyan, SW Shih, HYM Liao IEEE transactions on multimedia 10 (8), 1578-1591, 2008 | 22 | 2008 |
Segmental multi-way local pooling for video recognition I Kim, S Oh, A Vahdat, K Cannons, AGA Perera, G Mori Proceedings of the 21st ACM international conference on Multimedia, 637-640, 2013 | 8 | 2013 |
Trecvid 2013 genie: Multimedia event detection and recounting S Oh, AGA Perera, I Kim, M Pandey, K Cannons, H Hajimirsadeghi, ... Parade 1 (26.0), 51.7, 2013 | 3 | 2013 |
Efficient video quality assessment based on spacetime texture representation P Peng, K Cannons, ZN Li Proceedings of the 21st ACM international conference on Multimedia, 641-644, 2013 | 3 | 2013 |
Signal classification through multifractal analysis and complex domain neural networks V Cheung, K Cannons, W Kinsner, J Pear CCECE 2003-Canadian Conference on Electrical and Computer Engineering …, 2003 | 3 | 2003 |
A Unifying Theoretical Framework for Region Tracking K Cannons, RP Wildes york university Technical Report, CSE-2013-04, 2013 | 1 | 2013 |
A biologically inspired gait recognition system using the Hough transform. K Cannons | 1 | 2004 |
Domain Adaptation in Crowd Counting MA Hossain, MKK Reddy, K Cannons, Z Xu, Y Wang 2020 17th Conference on Computer and Robot Vision (CRV), 150-157, 2020 | | 2020 |