Multiple Objects Tracking Based on Linear Fitting

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Abstract:

For multiple objects tracking in complex scenes, a new tracking algorithm based on linear fitting for multiple moving objects is proposed. DG_CENTRIST feature and color feature are combined to describe the object, and the overlapping ratio of the tracking object is calculated. The object in the current frame is measured by using coincidence degree. If there is occlusion, we predict the path of each object by linear fitting and adjust the results of tracking in order to get correct results. The experiment results show that this method can effectively improve the accuracy of the multiple target tracking.

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1438-1441

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] P. Viola, M. Jones: Rapid Object Detection using a Boosted Cascade of Simple Features. IEEE Conference on Computer Vision and Pattern Recognition (2001).

DOI: 10.1109/cvpr.2001.990517

Google Scholar

[2] Y. Rui, Y. Chen: Better Proposal Distributions: Object Tracking Using Unscented Particle Filter. IEEE Conference on Computer Vision and Pattern Recognition (2011), pp.786-793.

DOI: 10.1109/cvpr.2001.991045

Google Scholar

[3] K. Okuma, A. Taleghani,N. De. Freitas: A boosted particle filter:multi-target detection and tracking. Proc of the European Conference on Computer Vision (2004), pp.28-39.

DOI: 10.1007/978-3-540-24670-1_3

Google Scholar

[4] J. Vermaak, A. Doucet, P. Perez: Maintaining Multi-Modality through Mixture Tracking. International Conference on Computer Vision (2003).

DOI: 10.1109/iccv.2003.1238473

Google Scholar

[5] J. Wu, Geyer, C. Rehe: Real-time human detection using contour cues. IEEE International Conference on Robotics and Automation (2011), pp.860-867.

DOI: 10.1109/icra.2011.5980437

Google Scholar