ECCV 2010 Tutorial
Ivan Laptev (INRIA / École Normale Supérieure)
Greg Mori (Simon Fraser University)
Tuesday 5 September 2010 AM
Creta Maris Hotel, Hersonissos, Crete
Resources
Datasets
Overview
Automatic
recognition of human actions and gestures is an important topic in
computer vision. Solving this problem is essential for a number of
emerging industries including indexing of professional and
user-generated video archives, automatic video surveillance, and
human-computer interaction. Moreover, understanding the function and
the meaning of many object and scene classes is intertwined with
understanding human actions which highlights the importance of action
recognition in solving other computer vision problems.
The
field of human action recognition has evolved considerably over the
recent years. Local video representations are now used extensively in
combination with statistical recognition methods. At the same time, new
powerful structural methods have emerged, presenting solutions to
action recognition based on recent advances in structured learning.
This course will give an introduction into novel trends in statistical
and structural action recognition and will illustrate ideas with
examples of successful methods from recent literature. In particular,
we will cover bag-of-features action recognition and will discuss
alternative local feature representations and their extensions. We will
consider current issues in human actions datasets and will address
weakly supervised and unsupervised approaches for human actions. We
will next present advances in structural modeling of human poses and
cover recent structured learning methods for action recognition. While
this course will mostly cover action recognition in video, we will also
discuss action recognition from still images such as in the Action
Classification Taster Competition of PASCAL VOC 2010.
Lecture Topics
- Introduction
- Human actions in science and applications
- Historical overview
- Problem definitions
- Datasets
- Statistical methods
- Early silhouette and tracking-based methods
- Motion-based similarity measures
- Template-based methods
- Local space-time features
- Bag-of-Features action recognition
- Weakly-supervised methods
- Structural methods
- Pose estimation and action recognition
- Action recognition in still images
- Human interactions and dynamic scene models
- Conclusions and future directions
Lecturer Biographies
Ivan Laptev is currently a full-time researcher in the WILLOW team at
INRIA – Paris and École Normale Supérieure (ENS). He received his PhD
in Computer Science from the Royal Institute of Technology (KTH) in
2004 and his Master of Science degree from the same institute in 1997.
He was a research assistant at the Technical University of Munich (TUM)
during 1997-1999 and he joined INRIA in 2004. Ivan’s main research
interests concern visual understanding of dynamic scenes including
recognition of human actions, scenes and object categories. Ivan has
published over 30 papers at international conferences and journals on
computer vision, he serves as an associate editor of Image and Vision
Computing Journal and as an area chair of CVPR 2010, he is a regular
member of program committees of major international conferences on
computer vision. Ivan has been awarded “Prime d’Excellence
Scientifique” in 2010.
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Greg Mori is currently an assistant
professor in the School of Computing Science at Simon Fraser
University. He received the Ph.D. degree in Computer Science from the
University of California, Berkeley in 2004. He received an Hon. B.Sc.
in Computer Science and Mathematics with High Distinction from the
University of Toronto in 1999. He spent one year (1997-1998) as an
intern at Advanced Telecommunications Research (ATR) in Kyoto, Japan.
Dr. Mori’s research interests are in computer vision, and include
object recognition, human activity recognition, human body pose
estimation. He serves on the program committee of major computer vision
conferences (CVPR, ECCV, ICCV), and was the program co-chair of the
Canadian Conference on Computer and Robot Vision (CRV) in 2006
and 2007. He is an Associate Editor for IEEE Transactions on Pattern
Analysis and Machine Intelligence (T-PAMI). Dr. Mori received the
Excellence in Undergraduate Teaching Award from the SFU Computing
Science Student Society in 2006. Dr. Mori received the Canadian Image Processing and Pattern Recognition Society (CIPPRS) Award for Research
Excellence and Service in 2008.
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