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Greg MoriAssociate ProfessorSchool of Computing Science Simon Fraser University 8888 University Drive Burnaby, BC CANADA V5A 1S6 Office: TASC1 8007 Phone: (778) 782-7111 Fax: (778) 782-3045 mori@cs.sfu.ca Ph.D. in Computer Science, University of California at Berkeley, 2004. Hon. B.Sc. in Computer Science and Mathematics, University of Toronto, 1999. |
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My research is in computer vision, and is concerned with developing
algorithms that automatically interpret images and videos,
particularly those containing people. I have made significant
contributions towards solving the problems of human pose estimation
and human action recognition. At a broad level, the methodology
followed is to construct features and representations that capture our
intuition regarding these vision problems. We operationalize these via
machine learning algorithms, adapting them to suit our
purposes.
Specific examples of features and representations include work on superpixels for representing images, motion features for human action recognition, and our bag-of- words model for video sequences. We have developed variants of machine learning algorithms for models such as the hidden Conditional Random Field (hCRF) and Latent Dirichlet Allocation (LDA) to implement these ideas. Research interests keywords:
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Tian Lan (PhD) had a paper accepted to IEEE Computer Vision and Pattern Recognition (CVPR), 2013. This work develops an image tag ranking algorithm that can determine which keywords are more relevant to a given image. |
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Guang-Tong Zhou, Tian Lan (PhD), and Weilong Yang had a paper accepted to IEEE Computer Vision and Pattern Recognition (CVPR), 2013. An image classification algorithm that matches a set of objects to an image is developed. |
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Yuke Zhu (BSc) and Tian Lan (PhD) had a paper on activity recognition accepted to IAPR Conference on Machine Vision Applications (MVA), 2013. Latent variable models were used to analyze nursing home surveillance video. |
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Weilong Yang successfully defended his Ph.D. thesis Discriminative Latent Variable Models For Visual Recognition. Congratulations Weilong! |
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Weilong Yang (PhD), and Arash Vahdat (PhD) had a paper accepted to Neural Information Processing Systems (NIPS) 2012. A kernelized latent SVM formulation is developed, and applied to various visual recognition problems. |
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Zhi Feng Huang successfully defended his M.Sc. thesis Latent Boosting For Action Recognition. Congratulations Zhi Feng! |
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Hossein Hajimirsadeghi (PhD) had a paper accepted to the IAPR International Conference on Pattern Recognition (ICPR), 2012. A boosting-based multiple instance learning algorithm is developed. The algorithm allows for varying degrees of bag-level positives in the multiple instance learning setup. |
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Nataliya Shapovalova (PhD), Arash Vahdat (PhD), Tian Lan (PhD) and Kevin Cannons (PDF) had a paper accepted to the European Conference on Computer Vision (ECCV), 2012. The work focuses on weakly-supervised action recognition in videos. We learn a model that can classify unseen test videos, as well as localize a region of interest in the video that captures the discriminative essence of the action class. |
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Tian Lan (PhD) and Weilong Yang (PhD) had a paper accepted to the European Conference on Computer Vision (ECCV), 2012. An image retrieval approach is developed. The approach allows queries specifying which objects, in which relations, should be present in an image. A learning algorithm for determining which object detectors and relations are most useful for retrieval is presented. |
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