Abstract
The recognition of continuous human activities performed with several limbs is still an open problem. We propose a novel approach for recognition of continuous activities, which considers the direction change between frames to track the motion of several limbs and uses a Bayesian network to recognize different activities. The approach presented can recognize activities performed at different velocities by different people. We tested the model with real image sequences for 3 different activities performed on a continuous way.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ismail Haritaoglu, David Harwood, and Larry S. Davis, “Ghost: A Human Body Part Labeling System Using Silhouettes”, Fourteenth International Conference on Pattern Recognition, Brisbane, August, 1998.
James W. Davis and Aarón F. Bobick, “The Representation and Recognition of Action Using Temporal Templates,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR’97), 1997.
Douglas Ayers and Shah Mubarak, “Monitoring Human Behavior in an Office Environtment,” Interpretation of Visual Motion Workshop, CVPR’98, june 1998.
Christoph Bregler, “Learning and Recognizing Human Dynamics in Video Sequences,” Proceedings IEEE Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, june, 1997.
Junji Yamato, Jun Ohya and Kenichiro Ishii, “Recognizing Human Action in Time-Sequential Images Using Hidden Markov Model, ” IEEE, 1992.
Stephen Intille and Aaron Bobick, “A Framework for Recognizing Multi-Agent Action from Visual Evidence,” M.I.T. Media Laboratory Perceptual Computing Section Technical Report No. 489, 1999.
Richard Neapolitan, “Probabilistic Reasoning in Intelligent Systems: Theory and Algorithms,” New York: Wiley, 1989.
Steve B. Cousins, William Chen, Mark E. Frisse, “CABeN: A Collection of Algorithms for Belief Networks” Medical Informatics Laboratory, Washington University, 1990.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Díaz de León, R., Enrique Sucar, L. (2002). Recognition of Continuous Activities. In: Garijo, F.J., Riquelme, J.C., Toro, M. (eds) Advances in Artificial Intelligence — IBERAMIA 2002. IBERAMIA 2002. Lecture Notes in Computer Science(), vol 2527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36131-6_89
Download citation
DOI: https://doi.org/10.1007/3-540-36131-6_89
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00131-7
Online ISBN: 978-3-540-36131-2
eBook Packages: Springer Book Archive