Abstract
In this paper we address the problem of on-line recognition of human activities taking place in a public area such as a shopping center. We consider standard activities; namely, entering, exiting, passing or browsing. The problem is motivated by surveillance applications, for which large numbers of cameras have been deployed in recent years. Such systems should be able to detect and recognize human activities, with as little human intervention as possible.
In this work, we model the displacement of a person in consecutive frames using a bank of switched dynamical systems, each of which tailored to the specific motion regimes that each trajectory may contain.
Our experimental results are based on nearly 20,000 images concerning four atomic activities and several complex ones, and demonstrate the effectiveness of the proposed approach.
This work was supported by Fundação para a Ciência e a Tecnologia (ISR/IST plurianual funding) through the POS Conhecimento Program which includes FEDER funds.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ayers, D., Shah, M.: Monitoring human behavior from video taken in an office environment. Image and Vision Computing 19, 833–846 (2001)
Bobick, A., Davis, J.: The recognition of human movement using temporal templates. IEEE Trans. on Patt. Anal. and Machine Intell. 23, 257–267 (2001)
Davis, J.: Sequential reliable inference for rapid detection of human actions. In: IEEE Conf. on Advance Video and Signal Based Surveillance, pp. 169–176 (2003)
Davis, J., Shah, M.: Visual gesture recognition. IEEE Proc. Vision, Image and Signal Processing 141, 101–106 (1994)
Efros, A., Berg, A., Mori, G., Malik, J.: Recognizing action at a distance. In: IEEE Int. Conf. on Comp. Vision, Nice, France, pp. 726–733 (2003)
Haritaoglu, I., Harwood, D., Davis, L.S.: W 4: real-time surveillance of people and their activities. IEEE Trans. on Patt. Anal. and Machine Intell. 22, 809–830 (2000)
Hongeng, S., Nevatia, R., Bremond, F.: Video-based event recognition: activity representation and probabilistic recognition methods. Computer Vision and Image Understanding 96, 129–162 (2004)
Hu, T., Tan, T., Wang, L., Maybank, S.: A survey on visual surveillance of object motion and behaviors. IEEE Trans. on Systems and Cybernetics: Applications and Reviews 34, 334–352 (2004)
Ivanov, Y., Bobick, A.: Recognition of visual activities and interactions by stochastic parsing. IEEE Trans. on Patt. Anal. and Machine Intell. 22, 852–872 (2000)
Liao, L., Fox, D., Kautz, H.: Learning and inferring transportation routines. In: Proc. National Conf. on Artificial Intelligence (2004)
Okuma, K., Taleghani, A., de Freitas, N., Little, J.J., Lowe, D.G.: A boosted particle filter: Multitarget detection and tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 28–39. Springer, Heidelberg (2004)
Oliver, N., Rosario, B., Pentland, A.: A Bayesian computer vision system for modeling human interactions. IEEE Trans. on Patt. Anal. and Machine Intell. 22, 831–843 (2000)
Rissanen, J.: Stochastic Complexity in Statistical Inquiry. World Scientific, Singapore (1989)
Rosales, R., Sclaroff, S.: 3D trajectory recovery for tracking multiple objects and trajectory guided recognition of actions. In: Proc. IEEE Conf. on Comp. Vision and Patt. Recognition, vol. 2, pp. 2117–2123 (1999)
Rosenblum, M., Yacoob, Y., Davis, L.S.: Human expression recognition from motion using a radial basis function network architecture. IEEE Trans. Neural Networks 7, 1121–1138 (1996)
Zhao, T., Nevatia, R.: Tracking multiple humans in complex situations. IEEE Trans. on Patt. Anal. and Machine Intell. 26, 1208–1221 (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Nascimento, J.C., Figueiredo, M.A.T., Marques, J.S. (2007). On-Line Classification of Human Activities. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_56
Download citation
DOI: https://doi.org/10.1007/978-3-540-72849-8_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
Online ISBN: 978-3-540-72849-8
eBook Packages: Computer ScienceComputer Science (R0)