BEYOND ACTIONS : DISCRIMINATIVE MODELS FOR CONTEXTUAL GROUP ACTIVITIES

@inproceedings{Li2010BEYONDA,
  title={BEYOND ACTIONS : DISCRIMINATIVE MODELS FOR CONTEXTUAL GROUP ACTIVITIES},
  author={Ze-Nian Li},
  year={2010}
}
Human action recognition from realistic videos is a challenging problem in computer vision. Several intrinsic properties such as intra-class variations, background clutter and partial occlusion make it difficult to recognize individual person actions reliably. In this dissertation, we go beyond recognizing individual person actions and focus on group activities instead. This motivates from the observation that human actions are rarely performed in isolation, the contextual information of what… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 120 CITATIONS

Bilinear Programming for Human Activity Recognition with Unknown MRF Graphs

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition
  • 2013
VIEW 14 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Automatic group activity annotation for mobile videos

VIEW 5 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Deep Structured Models For Group Activity Recognition

  • BMVC
  • 2015
VIEW 6 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Discriminative Context Models for Collective Activity Recognition

  • 2014 22nd International Conference on Pattern Recognition
  • 2014
VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Understanding Collective Activitiesof People from Videos

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2014
VIEW 5 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Consistent collective activity recognition with fully connected CRFs

  • Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012)
  • 2012
VIEW 4 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

Learning Human Interaction by Interactive Phrases

VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2011
2019

CITATION STATISTICS

  • 20 Highly Influenced Citations

  • Averaged 6 Citations per year from 2017 through 2019

References

Publications referenced by this paper.
SHOWING 1-10 OF 51 REFERENCES

What are they doing? : Collective activity classification using spatio-temporal relationship among people

  • 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops
  • 2009
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2009
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

A discriminatively trained, multiscale, deformable part model

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Learning realistic human actions from movies

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Actions as Space-Time Shapes

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2007
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Recognizing human actions: a local SVM approach

  • Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
  • 2004
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Discriminative models for static human-object interactions

  • 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
  • 2010
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Modelling activity global temporal dependencies using Time Delayed Probabilistic Graphical Model

  • 2009 IEEE 12th International Conference on Computer Vision
  • 2009
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL