Multi person detection and tracking based on hierarchical level-set method

Chadia Khraief; Faouzi Benzarti; Hamid Amiri

doi:10.1117/12.2310149

13 April 2018 Multi person detection and tracking based on hierarchical level-set method

Chadia Khraief, Faouzi Benzarti, Hamid Amiri

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106960G (2018) https://doi.org/10.1117/12.2310149
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

Citation Download Citation

Chadia Khraief, Faouzi Benzarti, and Hamid Amiri "Multi person detection and tracking based on hierarchical level-set method", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960G (13 April 2018); https://doi.org/10.1117/12.2310149

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