Person reidentification on video surveillance data

Andrey Kuznetsov

doi:10.1117/12.2522932

15 March 2019 Person reidentification on video surveillance data

Andrey Kuznetsov

Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110410P (2019) https://doi.org/10.1117/12.2522932
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany

Abstract

Person reidentification is a very challenging problem nowadays because of a big amount of video surveillance systems used. The data from such systems is processed to analyze events or emergency situations, find specific people, etc. One of the ways of solving the problem of an area security is the development of person reidentification algorithms. In this paper we propose an algorithm for person reidentification based on RGB histogram features calculation. On the first stage HOG descriptor is selected to detect a person on an image. Then we used k-means++ clustering algorithm to remove background on a person image. Finally, Bayes and SVM classification methods were used for person reidentification. Experimental results showed that the proposed solution can be used for person reidentification with high precision (not less than 82%). To carry out research 3D People Surveillance Dataset was used.

Citation Download Citation

Andrey Kuznetsov "Person reidentification on video surveillance data", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410P (15 March 2019); https://doi.org/10.1117/12.2522932

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