4W1H and Particle Swarm Optimization for Human  Activity Recognition

Leon Palafox; Hideki Hashimoto

doi:10.20965/jaciii.2011.p0793

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JACIII Vol.15 No.7 pp. 793-799

doi: 10.20965/jaciii.2011.p0793

(2011)

Paper:

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4W1H and Particle Swarm Optimization for Human Activity Recognition

Leon Palafox and Hideki Hashimoto

Institute of Industrial Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:

February 21, 2011

Accepted:

May 27, 2011

Published:

September 20, 2011

Keywords:

self organizing maps, particle swarm optimization, 4W1H, activity recognition

Abstract

This paper proposes a paradigm in the forensic area for detecting and categorizing human activities. The presented approach uses five base variables, referred to as 4W1H (“Who,” “When,” “What,” “Where,” and “How”) to describe the context in an environment. The proposed system uses self-organizing maps to classify movements for the “How” variable of 4W1H, as well as particle swarm optimization clustering techniques for the grouping (clustering) of data obtained from observations. The paper describes the hardware settings required for detecting these variables and the system designed to do the sensing.

Cite this article as:

L. Palafox and H. Hashimoto, “4W1H and Particle Swarm Optimization for Human Activity Recognition,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.7, pp. 793-799, 2011.

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References

[1] J. H. Lee and H. Hashimoto, “Intelligent Space concept and contents,” Advanced Robotics, Vol.16, No.3, pp. 265-280, 2002.
[2] N. Robertson and I. Reid, “A general method for human activity recognition in video,” Computer Vision and Image Understanding, Vol.104, No.2-3, Special Issue on Modeling People: Vision-based understanding of a person’s shape, appearance, movement and behaviour, pp. 232-248, 2006.
[3] L. J. Li and L. Fei-Fei, “What, where and who? classifying events by scene and object recognition,” In Computer Vision, 2007, ICCV 2007. IEEE 11th Int. Conf. on, pp. 1-8, IEEE, 2007.
[4] P.-C. Huang, S.-S. Lee, Y.-H. Kuo, and K.-R. Lee, “A flexible sequence alignment approach on pattern mining and matching for human activity recognition,” Expert Systems with Applications, Vol.37, No.1, pp. 298-306, 2010.
[5] S. Chaplot, L. M. Patnaik, and N. R. Jagannathan, “Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network,” Biomedical Signal Processing and Control, Vol.1, No.1, pp. 86-92, 2006.
[6] B. N. Schilit and M. M. Theimer, “Disseminating active map information to mobile hosts. Network,” IEEE, Vol.8, No.5, pp. 22-32, 1994.
[7] A. Schmidt, “Implicit human computer interaction through context,” Personal and Ubiquitous Computing, Vol.4, No.2, pp. 191-199, 2000.
[8] T. Kohonen, “Self-organization and associative memories,” Heidelberger: Springer, 1982.
[9] H. Benitez-Perez, F. Garcia-Nocetti, and H. Thompson, “Fault classification SOMand PCA for inertial sensor drift,” In Intelligent Signal Processing, 2005 IEEE Int. Workshop on, pp. 177-182, IEEE, 2005.
[10] J. Kennedy, R. C. Eberhart et al., “Particle swarm optimization,” In Proc. of IEEE Int. Conf. on neural networks, Vol.4, pp. 1942-1948, Perth, Australia, 1995.
[11] M. Omran, A. Salman, and A. P. Engelbrecht, “Image classification using particle swarm optimization,” In Proc. of the 4th Asiapacific Conf. on Simulated Evolution and Learning, Vol.2002, pp. 370-374, 2002.
[12] M. Frazier, “An introduction to wavelets through linear algebra,” Undergraduate texts in mathematics, Springer, 1999.
[13] K. M. Cheung, “Developing the interview protocol for videorecorded child sexual abuse investigations: A training experience with police officers, social workers, and clinical psychologists in Hong Kong,” Child abuse & neglect, Vol.21, No.3, pp. 273-284, 1997.
[14] M. Niitsuma, K. Yokoi, and H. Hashimoto, “Describing humanobject interaction in intelligent space,” In HSI’09: Proc. of the 2nd Conf. on Human System Interactions, pp. 392-396, Piscataway, NJ, USA, IEEE Press, 2009.
[15] L. Palafox and H. Hashimoto, “A human movement profile classifier using Self Organized Maps in the 4W1H architecture,” In Proc. RSJ 27th Annual Conf., 2009.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] J. H. Lee and H. Hashimoto, “Intelligent Space concept and contents,” Advanced Robotics, Vol.16, No.3, pp. 265-280, 2002.

[2] [2] N. Robertson and I. Reid, “A general method for human activity recognition in video,” Computer Vision and Image Understanding, Vol.104, No.2-3, Special Issue on Modeling People: Vision-based understanding of a person’s shape, appearance, movement and behaviour, pp. 232-248, 2006.

[3] [3] L. J. Li and L. Fei-Fei, “What, where and who? classifying events by scene and object recognition,” In Computer Vision, 2007, ICCV 2007. IEEE 11th Int. Conf. on, pp. 1-8, IEEE, 2007.

[4] [4] P.-C. Huang, S.-S. Lee, Y.-H. Kuo, and K.-R. Lee, “A flexible sequence alignment approach on pattern mining and matching for human activity recognition,” Expert Systems with Applications, Vol.37, No.1, pp. 298-306, 2010.

[5] [5] S. Chaplot, L. M. Patnaik, and N. R. Jagannathan, “Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network,” Biomedical Signal Processing and Control, Vol.1, No.1, pp. 86-92, 2006.

[6] [6] B. N. Schilit and M. M. Theimer, “Disseminating active map information to mobile hosts. Network,” IEEE, Vol.8, No.5, pp. 22-32, 1994.

[7] [7] A. Schmidt, “Implicit human computer interaction through context,” Personal and Ubiquitous Computing, Vol.4, No.2, pp. 191-199, 2000.

[8] [8] T. Kohonen, “Self-organization and associative memories,” Heidelberger: Springer, 1982.

[9] [9] H. Benitez-Perez, F. Garcia-Nocetti, and H. Thompson, “Fault classification SOMand PCA for inertial sensor drift,” In Intelligent Signal Processing, 2005 IEEE Int. Workshop on, pp. 177-182, IEEE, 2005.

[10] [10] J. Kennedy, R. C. Eberhart et al., “Particle swarm optimization,” In Proc. of IEEE Int. Conf. on neural networks, Vol.4, pp. 1942-1948, Perth, Australia, 1995.

[11] [11] M. Omran, A. Salman, and A. P. Engelbrecht, “Image classification using particle swarm optimization,” In Proc. of the 4th Asiapacific Conf. on Simulated Evolution and Learning, Vol.2002, pp. 370-374, 2002.

[12] [12] M. Frazier, “An introduction to wavelets through linear algebra,” Undergraduate texts in mathematics, Springer, 1999.

[13] [13] K. M. Cheung, “Developing the interview protocol for videorecorded child sexual abuse investigations: A training experience with police officers, social workers, and clinical psychologists in Hong Kong,” Child abuse & neglect, Vol.21, No.3, pp. 273-284, 1997.

[14] [14] M. Niitsuma, K. Yokoi, and H. Hashimoto, “Describing humanobject interaction in intelligent space,” In HSI’09: Proc. of the 2nd Conf. on Human System Interactions, pp. 392-396, Piscataway, NJ, USA, IEEE Press, 2009.

[15] [15] L. Palafox and H. Hashimoto, “A human movement profile classifier using Self Organized Maps in the 4W1H architecture,” In Proc. RSJ 27th Annual Conf., 2009.