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A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis

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Abstract

Tracking of moving objects in real situation is a challenging research issue, due to dynamic changes in objects or background appearance, illumination, shape and occlusions. In this paper, we deal with these difficulties by incorporating an adaptive feature weighting mechanism to the proposed growing competitive neural network for multiple objects tracking. The neural network takes advantage of the most relevant object features (information provided by the proposed adaptive feature weighting mechanism) in order to estimate the trajectories of the moving objects. The feature selection mechanism is based on a genetic algorithm, and the tracking algorithm is based on a growing competitive neural network where each unit is associated to each object in the scene. The proposed methods (object tracking and feature selection mechanism) are applied to detect the trajectories of moving vehicles in roads. Experimental results show the performance of the proposed system compared to the standard Kalman filter.

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Notes

  1. Datasets of NGSIM are available at http://ngsim-community.org/

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Acknowledgments

This work is partially supported by the Ministry of Economy and Competitiveness of Spain under grant TIN2011-24141, project name Detection of anomalous activities in video sequences by self-organizing neural systems, and the Autonomous Government of Andalusia (Spain) under project P12-TIC-6213, project name Development of Self-Organizing Neural Networks for Information Technologies.

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Authors and Affiliations

  1. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071 , Malaga, Spain

    Rafael M. Luque-Baena, Juan M. Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio, Enrique Domínguez & Esteban J. Palomo

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  1. Rafael M. Luque-Baena
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  2. Juan M. Ortiz-de-Lazcano-Lobato
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  3. Ezequiel López-Rubio
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  4. Enrique Domínguez
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  5. Esteban J. Palomo
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Correspondence to Rafael M. Luque-Baena.

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Luque-Baena, R.M., Ortiz-de-Lazcano-Lobato, J.M., López-Rubio, E. et al. A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis. Neural Process Lett 37, 47–67 (2013). https://doi.org/10.1007/s11063-012-9268-3

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  • DOI: https://doi.org/10.1007/s11063-012-9268-3

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