[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7236/IJIBC.2021.13.2.156

Object Tracking with Histogram weighted Centroid augmented Siamese Region Proposal Network

Budiman, Sutanto Edward (Supersell Co. Ltd)
Lee, Sukho (Dept. Information Communications Engineering, Dongseo University)

Publication Information

International Journal of Internet, Broadcasting and Communication / v.13, no.2, 2021 , pp. 156-165 More about this Journal

Abstract

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

Keywords

Siamese network; Histogram; Deep learning; Object Tracking;

Citations & Related Records

Reference

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